A vehicle occupant monitoring system, OMS, comprises an image acquisition device with a rolling shutter image sensor configured to selectively operate in either: a full-resolution image mode where an image frame corresponding to the full image sensor is provided; or a region of interest, ROI, mode, where an image frame corresponding to a limited portion of the image sensor is provided. An object detector is configured to receive a full-resolution image from the image sensor and to identify a ROI corresponding to an object of interest within the image. A controller is configured to obtain an image corresponding to the ROI from the image sensor operating in ROI mode, the image having an exposure time long enough for all rows of the ROI to be illuminated by a common pulse of light from at least one infra-red light source and short enough to limit motion blur within the image.
G06V 10/143 - Détection ou éclairage à des longueurs d’onde différentes
G06V 10/147 - Caractéristiques optiques de l’appareil qui effectue l’acquisition ou des dispositifs d’éclairage - Détails de capteurs, p.ex. lentilles de capteurs
G06V 10/25 - Détermination d’une région d’intérêt [ROI] ou d’un volume d’intérêt [VOI]
G06V 10/60 - Extraction de caractéristiques d’images ou de vidéos relative aux propriétés luminescentes, p.ex. utilisant un modèle de réflectance ou d’éclairage
G06V 20/59 - Contexte ou environnement de l’image à l’intérieur d’un véhicule, p.ex. concernant l’occupation des sièges, l’état du conducteur ou les conditions de l’éclairage intérieur
G06V 10/98 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos Évaluation de la qualité des motifs acquis
A method for identifying a gesture from one of a plurality of dynamic gestures, each dynamic gesture comprising a distinct movement made by a user over a period of time within a field of view of an image acquisition device comprises iteratively: acquiring a current image from said image acquisition device at a given time; and passing at least a portion of the current image through a bidirectionally recurrent multi-layer classifier. A final layer of the multi-layer classifier comprises an output indicating a probability that a gesture from the plurality of dynamic gestures is being made by a user during the time of acquiring the image.
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 40/20 - Mouvements ou comportement, p.ex. reconnaissance des gestes
A method for monitoring occupants of a vehicle comprises identifying a respective body region for one or more occupants of the vehicle within an obtained image; identifying within the body regions, skeletal points including points on an arm of a body; identifying one or more hand regions; and determining a hand region to be either a left or a right hand of an occupant in accordance with its spatial relationship with identified skeletal points of the body region of an occupant. The left or right hand region for the occupant are provided to a pair of classifiers to provide an activity classification for the occupant, a first classifier being trained with images of hands of occupants in states where objects involved are not visible and a second classifier being trained with images of occupants in the states where the objects are visible in at least one hand region.
G06V 20/59 - Contexte ou environnement de l’image à l’intérieur d’un véhicule, p.ex. concernant l’occupation des sièges, l’état du conducteur ou les conditions de l’éclairage intérieur
G06V 40/10 - Corps d’êtres humains ou d’animaux, p.ex. occupants de véhicules automobiles ou piétons; Parties du corps, p.ex. mains
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
A method for calibrating a vehicle cabin camera having: a pitch, yaw and roll angle; and a field of view capturing vehicle cabin features which are symmetric about a vehicle longitudinal axis comprises: selecting points from within an image of the vehicle cabin and projecting the points onto a 3D unit circle in accordance with a camera projection model. For each of one or more rotations of a set of candidate yaw and roll rotations, the method comprises: rotating the projected points with the rotation; flipping the rotated points about a pitch axis; counter-rotating the projected points with an inverse of the rotation; and mapping the counter-rotated points back into an image plane to provide a set of transformed points. A candidate rotation which provides a best match between the set of transformed points and the locations of the selected points in the image plane is selected.
A method comprises displaying a first image acquired from a camera having an input camera projection model including a first focal length and an optical axis parameter value. A portion of the first image is selected as a second image associated with an output camera projection model in which either a focal length and/or an optical axis parameter value differ from the parameters of the input camera projection model. The method involves iteratively: adjusting either the focal length and/or an optical axis parameter value for the camera lens so that it approaches the corresponding value of the output camera projection model; acquiring a subsequent image using the adjusted focal length or optical axis parameter value; mapping pixel coordinates in the second image, through a normalized 3D coordinate system to respective locations in the subsequent image to determine respective values for the pixel coordinates; and displaying the second image.
Disclosed is a multi-modal convolutional neural network (CNN) for fusing image information from a frame based camera, such as, a near infra-red (NIR) camera and an event camera for analysing facial characteristics in order to produce classifications such as head pose or eye gaze. The neural network processes image frames acquired from each camera through a plurality of convolutional layers to provide a respective set of one or more intermediate images. The network fuses at least one corresponding pair of intermediate images generated from each of image frames through an array of fusing cells. Each fusing cell is connected to at least a respective element of each intermediate image and is trained to weight each element from each intermediate image to provide the fused output. The neural network further comprises at least one task network configured to generate one or more task outputs for the region of interest.
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
G06V 10/80 - Fusion, c. à d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
G06V 20/59 - Contexte ou environnement de l’image à l’intérieur d’un véhicule, p.ex. concernant l’occupation des sièges, l’état du conducteur ou les conditions de l’éclairage intérieur
7.
PRODUCING AN IMAGE FRAME USING DATA FROM AN EVENT CAMERA
A method of producing an image frame from event packets received from an event camera comprises: forming a tile buffer sized to accumulate event information for a subset of image tiles, the tile buffer having an associated tile table that determines a mapping between each tile of the image frame for which event information is accumulated in the tile buffer and the image frame. For each event packet: an image tile corresponding to the pixel location of the event packet is identified; responsive to the tile buffer storing information for one other event corresponding to the image tile, event information is added to the tile buffer; and responsive to the tile buffer not storing information for another event corresponding to the image tile and responsive to the tile buffer being capable of accumulating event information for at least one more tile, the image tile is added to the tile buffer.
H04N 5/335 - Transformation d'informations lumineuses ou analogues en informations électriques utilisant des capteurs d'images à l'état solide [capteurs SSIS]
A method to determine activity in a sequence of successively acquired images of a scene, comprises: acquiring the sequence of images; for each image in the sequence of images, forming a feature block of features extracted from the image and determining image specific information including a weighting for the image; normalizing the determined weightings to form a normalized weighting for each image in the sequence of images; for each image in the sequence of images, combining the associated normalized weighting and associated feature block to form a weighted feature block; passing a combination of the weighted feature blocks through a predictive module to determine an activity in the sequence of images; and outputting a result comprising the determined activity in the sequence of images.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
A method for producing a textural image from event information generated by an event camera comprises: accumulating event information from a plurality of events occurring during successive event cycles across a field of view of the event camera, each event indicating an x,y location within the field of view, a polarity for a change of detected light intensity incident at the x,y location and an event cycle at which the event occurred; in response to selected event cycles, analysing event information for one or more preceding event cycles to identify one or more regions of interest bounding a respective object to be tracked; and responsive to a threshold event criterion for a region of interest being met, generating a textural image for the region of interest from event information accumulated from within the region of interest.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
10.
METHOD AND SYSTEM TO DETERMINE THE LOCATION AND/OR ORIENTATION OF A HEAD
A method for determining an absolute depth map to monitor the location and pose of a head (100) being imaged by a camera comprises: acquiring (20) an image from the camera (110) including a head with a facial region; determining (23) at least one distance from the camera (110) to a facial feature of the facial region using a distance measuring sub-system (120); determining (24) a relative depth map of facial features within the facial region; and combining (25) the relative depth map with the at least one distance to form an absolute depth map for the facial region.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
A camera comprises a lens assembly coupled to an event-sensor, the lens assembly being configured to focus a light field onto a surface of the event-sensor, the event-sensor surface comprising a plurality of light sensitive-pixels, each of which cause an event to be generated when there is a change in light intensity greater than a threshold amount incident on the pixel. The camera further includes an actuator which can be triggered to cause a change in the light field incident on the surface of the event-sensor and to generate a set of events from a sub-set of pixels distributed across the surface of the event-sensor.
G06K 9/60 - Combinaison de l'obtention de l'image et des fonctions de prétraitement
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
H04N 5/341 - Extraction de données de pixels provenant d'un capteur d'images en agissant sur les circuits de balayage, p.ex. en modifiant le nombre de pixels ayant été échantillonnés ou à échantillonner
A neural network image processing apparatus arranged to acquire images from an image sensor and to: identify a ROI containing a face region in an image; determine at plurality of facial landmarks in the face region; use the facial landmarks to transform the face region within the ROI into a face region having a given pose; and use transformed landmarks within the transformed face region to identify a pair of eye regions within the transformed face region. Each identified eye region is fed to a respective first and second convolutional neural network, each network configured to produce a respective feature vector. Each feature vector is fed to respective eyelid opening level neural networks to obtain respective measures of eyelid opening for each eye region. The feature vectors are combined and to a gaze angle neural network to generate gaze yaw and pitch values substantially simultaneously with the eyelid opening values.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
In an embodiment, a 3D facial modeling system includes a plurality of cameras configured to capture images from different viewpoints, a processor, and a memory containing a 3D facial modeling application and parameters defining a face detector, wherein the 3D facial modeling application directs the processor to obtain a plurality of images of a face captured from different viewpoints using the plurality of cameras, locate a face within each of the plurality of images using the face detector, wherein the face detector labels key feature points on the located face within each of the plurality of images, determine disparity between corresponding key feature points of located faces within the plurality of images, and generate a 3D model of the face using the depth of the key feature points.
A method for correcting an image divides an output image into a grid with vertical sections of width smaller than the image width but wide enough to allow efficient bursts when writing distortion corrected line sections into memory. A distortion correction engine includes a relatively small amount of memory for an input image buffer but without requiring unduly complex control.The input image buffer accommodates enough lines of an input image to cover the distortion of a single most vertically distorted line section of the input image. The memory required for the input image buffer can be significantly less than would be required to store all the lines of a distorted input image spanning a maximal distortion of a complete line within the input image.
A peripheral processing device comprises a physical interface for connecting the processing device to a host computing device through a communications protocol. A local controller connected to local memory across an internal bus provides input/output access to data stored on the processing device to the host through a file system API. A neural processor comprises at least one network processing engine for processing a layer of a neural network according to a network configuration. A memory at least temporarily stores network configuration information, input image information, intermediate image information and output information produced by each network processing engine. The local controller is arranged to receive network configuration information through a file system API write command, to receive input image information through a file system API write command; and to write output information to the local memory for retrieval by the host through a file system API read command.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06N 3/06 - Réalisation physique, c. à d. mise en œuvre matérielle de réseaux neuronaux, de neurones ou de parties de neurone
16.
SYSTEMS AND METHODS FOR HYBRID DEPTH REGULARIZATION
Systems and methods for hybrid depth regularization in accordance with various embodiments of the invention are disclosed. In one embodiment of the invention, a depth sensing system comprises a plurality of cameras; a processor; and a memory containing an image processing application. The image processing application may direct the processor to obtain image data for a plurality of images from multiple viewpoints, the image data comprising a reference image and at least one alternate view image; generate a raw depth map using a first depth estimation process, and a confidence map; and generate a regularized depth map. The regularized depth map may be generated by computing a secondary depth map using a second different depth estimation process; and computing a composite depth map by selecting depth estimates from the raw depth map and the secondary depth map based on the confidence map.
An iris image acquisition system (10) comprises an image sensor (14) comprising an array of pixels including pixels sensitive to NIR wavelengths; at least one NIR light source (16, 18) capable of selectively emitting light with different discrete NIR wavelengths; and a processor (20), operably connected to the image sensor (14) and the at least one NIR light source (16, 18), to acquire image information from the sensor (14) under illumination at one of the different discrete NIR wavelengths. A lens assembly (12) comprises a plurality of lens elements with a total track length of no more than 4.7mm, each lens element comprising a material with a refractive index inversely proportional to wavelength. The different discrete NIR wavelengths are matched with the refractive index of the material for the lens elements to balance axial image shift induced by a change in object distance with axial image shift due to change in illumination wavelength.
G02B 27/00 - Systèmes ou appareils optiques non prévus dans aucun des groupes ,
G02B 13/00 - Objectifs optiques spécialement conçus pour les emplois spécifiés ci-dessous
G02B 13/14 - Objectifs optiques spécialement conçus pour les emplois spécifiés ci-dessous à utiliser avec des radiations infrarouges ou ultraviolettes
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
G02B 13/18 - Objectifs optiques spécialement conçus pour les emplois spécifiés ci-dessous avec des lentilles ayant une ou plusieurs surfaces non sphériques, p.ex. pour réduire l'aberration géométrique
18.
A METHOD FOR PRODUCING A HISTOGRAM OF ORIENTED GRADIENTS
A method for producing a histogram of oriented gradients (HOG) for at least a portion of an image comprises dividing the image portion into cells, each cell comprising a plurality of image pixels. Then, for each image pixel of a cell, obtaining a horizontal gradient component, gx, and a vertical gradient component, gy, based on differences in pixel values along at least a row of the image and a column of the image respectively including the pixel; and allocating a gradient to one of a plurality of sectors, where n is a sector index, each sector extending through a range of orientation angles and at least some of the sectors being divided from adjacent sectors according to the inequalities: b*16
A biometric recognition system for a hand held computing device incorporating an inertial measurement unit (IMU) comprising a plurality of accelerometers and at least one gyroscope is disclosed. A tremor analysis component is arranged to: obtain from the IMU, accelerometer signals indicating device translational acceleration along each of X, Y and Z axes as well as a gyroscope signal indicating rotational velocity about the Y axis during a measurement window. Each of the IMU signals is filtered to provide filtered frequency components for the signals during the measurement window. The accelerometer signals are combined to provide a combined filtered accelerometer magnitude signal for the measurement window. A spectral density estimationis provided for each of the combined filtered accelerometer magnitude signal and the filtered gyroscope signal. An irregularity is determined for each spectral density estimation; and based on the determined irregularities, the tremor analysis component attempts to authenticate a user of the device.
G06F 21/32 - Authentification de l’utilisateur par données biométriques, p.ex. empreintes digitales, balayages de l’iris ou empreintes vocales
G06F 21/40 - Authentification de l’utilisateur sous réserve d’un quorum, c. à d. avec l’intervention nécessaire d’au moins deux responsables de la sécurité
20.
IMAGE PROCESSING METHOD AND SYSTEM FOR IRIS RECOGNITION
An image processing method for iris recognition of a predetermined subject, comprises acquiring through an image sensor, a probe image illuminated by an infra-red (IR) illumination source, wherein the probe image comprises one or more eye regions and is overexposed until skin portions of the image are saturated. One or more iris regions are identified within the one or more eye regions of said probe image; and the identified iris regions are analysed to detect whether they belong to the predetermined subject.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
A method of correcting an image obtained by an image acquisition device includes obtaining successive measurements (Gn), of device movement during exposure of each row of an image. An integration range (idx), is selected in proportion to an exposure time (te), for each row of the image. Accumulated measurements (Cn), of device movement for each row of an image are averaged across the integration range to provide successive filtered measurements (Ḡ), of device movement during exposure of each row of an image. The image is corrected for device movement using the filtered measurements (Ḡ).
A method operable within an image capture device for stabilizing a sequence of images captured by the image capture device is disclosed. The method comprises,using lens based sensors indicating image capture device movement during image acquisition, performing optical image stabilization (OIS) during acquisition of each image of the sequence of images to provide a sequence of OIS corrected images. Movement of the device for each frame during which each OIS corrected image is captured is determined using inertial measurement sensors. At least an estimate of OIS control performed during acquisition of an image is obtained. The estimate is removed from the intra-frame movement determined for the frame during which the OIS corrected image was captured to provide a residual measurement of movement for the frame. Electronic image stabilization (EIS) of each OIS corrected image based on the residual measurement is performed to provide a stabilized sequence of images.
A convolutional neural network (CNN) for an image processing system comprises an image cache responsive to a request to read a block of NxM pixels extending from a specified location within an input map to provide a block of NxM pixels at an output port. A convolution engine reads blocks of pixels from the output port, combines blocks of pixels with a corresponding set of weights to provide a product, and subjects the product to an activation function to provide an output pixel value. The image cache comprises a plurality of interleaved memories capable of simultaneously providing the NxM pixels at the output port in a single clock cycle. A controller provides a set of weights to the convolution engine before processing an input map, causes the convolution engine to scan across the input map by incrementing a specified location for successive blocks of pixels and generates an output map within the image cache by writing output pixel values to successive locations within the image cache.
An image processing system comprises a template matching engine (TME). The TME reads an image from the memory; and as each pixel of the image is being read, calculates a respective feature value of a plurality of feature maps as a function of the pixel value. A pre-filter is responsive to a current pixel location comprising a node within a limited detector cascade to be applied to a window within the image to: compare a feature value from a selected one of the plurality of feature maps corresponding to the pixel location to a threshold value; and responsive to pixels for all nodes within a limited detector cascade to be applied to the window having been read, determine a score for the window. A classifier, responsive to the pre-filter indicating that a score for a window is below a window threshold, does not apply a longer detector cascade to the window before indicating that the window does not comprise an object to be detected.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
A method of tracking an object across a stream of images comprises determining a region of interest (ROI) bounding the object in an initial frame of an image stream. A HOG map is provided for the ROI by: dividing the ROI into an array of MxN cells, each cell comprising a plurality of image pixels;and determining a HOG for each of the cells. The HOG map is stored as indicative of the features of the object. Subsequent frames are acquired from the stream of images. The frames are scanned ROI by ROI to identify a candidate ROI having a HOG map best matching the stored HOG map features. If the match meets a threshold, the stored HOG map indicative of the features of the object is updated according to the HOG map for the best matching candidate ROI.
An image processing apparatus comprises a normalisation module operatively connected across a bus to a memory storing an image in which a region of interest (ROI) has been identified within the image. The ROI is bound by a rectangle having a non-orthogonal orientation within the image. In one embodiment, the normalisation module is arranged to divide the ROI into one or more slices, each slice comprising a plurality of adjacent rectangular tiles. For each slice, the apparatus successively reads ROI information for each tile from the memory including: reading a portion of the image extending across at least a width of the slice line-by-line along an extent of a slice. For each tile, the apparatus downsamples the ROI information to a buffer to within a scale SD<2 of a required scale for a normalised version of the ROI. The apparatus then fractionally downsamples and rotates downsampled information for a tile within the buffer to produce a respective normalised portion of the ROI at the required scale for the normalised ROI. Downsampled and rotated information is accumulated for each tile within a normalised ROI buffer for subsequent processing by the image processing apparatus.
An image acquisition system for acquiring iris images for use in biometric recognition of a subject includes an optical system comprising a cluster of at least 2 lenses arranged in front of a common image sensor with each lens optical axis in parallel spaced apart relationship. Each lens has a fixed focus and a different aperture to provide a respective angular field of view. The lens with the closest focus has the smallest aperture and the lens with the farthest focus has the largest aperture so that iris images can be acquired across a focal range of at least from 200mm to 300mm.
G02B 27/00 - Systèmes ou appareils optiques non prévus dans aucun des groupes ,
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
28.
A METHOD AND APPARATUS FOR PRODUCING A VIDEO STREAM
A method of processing a stream of images comprises obtaining an image of a scene with a relatively short exposure time (SET) and obtaining an image of the same scene with a relatively longer exposure time (LET). Motion blur characteristics for the SET image corresponding to motion within the LET image are determined and the motion blur characteristics are applied to the SET image. The blurred SET image and the LET image are blended to provide a HDR image. The process is repeated for successive pairs of images in the stream to provide a sequence of HDR images which can be encoded in a video stream.
A method is disclosed for processing at least a portion of an input digital image comprising rows of pixels extending in two mutually perpendicular directions over a 2D field. The method comprises defining a kernel for processing an image, the kernel comprising at least one row of contiguous elements of the same non-zero value (such rows being referred to herein as equal-valued kernel regions), the equal-valued kernel regions, if more than one, extending parallel to one another. For each pixel in at least selected parallel rows of pixels within the image portion, the cumulative sum of the pixel is calculated by adding a value of the pixel to the sum of all preceding pixel values in the same row of the image portion. The kernel is convolved with the image portion at successive kernel positions relative to the image portion such that each pixel in each selected row is a target pixel for a respective kernel position. For each kernel position, the convolving is performed, for each equal-valued kernel region, by calculating the difference between the cumulative sum of the pixel corresponding to the last element in the equal-valued kernel region and the cumulative sum of the pixel corresponding to the element immediately preceding the first element in the region, and summing the differences for all equal-valued kernel regions. The differences sum is scaled to provide a processed target pixel value.
An image acquisition method operates in a hand held image acquisition device with a camera. A first image of a scene is obtained with the camera at a nominal exposure level. A number of relatively bright pixels and a number of relatively dark pixels within the first image are determined. Based on the number of relatively bright pixels, a negative exposure adjustment is determined and based on the number of relatively dark pixels, a positive exposure adjustment is determined. Respective images are acquired at the nominal exposure level; with the negative exposure adjustment; and with the positive exposure adjustment as component images for high dynamic range (HDR) image of the scene.
An image processing method operable in a hand held image acquisition device comprising at least one camera comprises obtaining an image with the camera and identifying at least one face region detected within the image. A mean intensity of intensity values for pixels of at least one identified face region is determined. Responsive to the mean intensity for a face region being less than a threshold amount, at least some of the pixels of the image are lightened. A contrast of pixels of the image is enhanced as a function of pixel intensity distribution within the image and a contrast of pixels of the face region is enhanced as a function of pixel intensity distribution within the face region. The contrast enhanced pixels of the face region are blended with pixels of the image which have been lightened and/or whose contrast has been enhanced to provide a processed image.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06K 9/22 - Obtention de l'image en utilisant des instruments déplacés manuellement
G06K 9/03 - Détection ou correction d'erreurs, p.ex. par une seconde exploration
An optical system for an image acquisition device comprises an image sensor comprising an array of pixels including pixels sensitive to IR wavelengths for acquiring an image. A lens assembly includes a collecting lens surface with an optical axis, the lens assembly being arranged to focus IR light received from a given object distance on the sensor surface. The lens assembly includes at least a first reflective surface for reflecting collected light along an axis transverse to the optical axis so that a length of the optical system along the optical axis is reduced by comparison to a focal length of the lens assembly.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
A method of processing an image comprises: acquiring an image of a scene including an object having a recognisable feature. A lens actuator setting providing a maximum sharpness for a region of the image including the object a nd a lens displacement corresponding to the lens actuator setting are determined. A distance to the object based on the lens displacement is calculated. A dimension of the feature as a function of the distance to the object, the imaged object size and a focal length of a lens assembly with which the image was acquired, is determined. The determined dimension of the feature is employed instead of an assumed dimension of the feature for subsequent processing of images of the scene including the object.
A method for producing a histogram of oriented gradients (HOG) for at least a portion of an image comprises dividing said image portion into cells, each cell comprising a plurality of image pixels. For each image pixel of a cell, a horizontal gradient component, gx, and a vertical gradient component, gy, is obtained based on differences in pixel values along at least a row of said image and a column of said image respectively including the pixel. A gradient is allocated to one of a plurality of sectors, each sector extending through a range of orientation angles. At least some of said sectors are divided from adjacent sectors along lines including gx=2n.gy, where n is any integer value with a magnitude greater than or equal to 1. At least one sector is associated with a bin; and a count of each instance of a pixel gradient of a cell associated with a bin is performed to provide a HOG for said cell.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
An optical system for an image acquisition device comprises a filter comprising a central aperture arranged to transmit both visible and selected near infra-red (NIR) wavelengths and a peripheral aperture arranged to block visible wavelengths and to transmit the NIR wavelengths. An image sensor comprises an array of pixels including pixels sensitive to visible wavelengths and corresponding pixels sensitive to the NIR wavelengths. A lens assembly is axially located between the filter and the image sensor and comprises a plurality of lens elements. The lens elements are arranged to simultaneously focus NIR light received from a given object through central and peripheral apertures of the filter and visible light received from the object through the central aperture onto the sensor surface.
G02B 13/14 - Objectifs optiques spécialement conçus pour les emplois spécifiés ci-dessous à utiliser avec des radiations infrarouges ou ultraviolettes
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
A method for calibrating an image capture device comprises mounting at least one sample device from a batch for movement through a plurality of orientations relative to a horizontal plane. For a given orientation, the sample device is focused at a sequence of positions, each position being at a respective focus distance from the device. A lens actuator setting is recorded for the sample device at each position. This is repeated at a plurality of distinct orientations of the sample device. Respective relationships are determined between lens actuator settings at any given position for distinct orientations from the plurality of distinct orientations and actuator settings at a selected orientation of the plurality of distinct orientations. Lens actuator settings for the image capture device to be calibrated are recorded at least at two points of interest (POI), each a specified focus distance from the device with the image capture device positioned at the selected orientation. The image capture device is calibrated for the plurality of distinct orientations based on the determined relationships and the recorded lens actuator settings.
A method of image processing within an image acquisition device comprises acquiring an image including one or more face regions and identifying one or more iris regions within the one or more face regions. The one or more iris regions are analyzed to identify any iris region comprising an iris pattern of sufficient quality to pose a risk of biometrically identifying a subject within the image. Responsive to identifying any such iris region, a respective substitute iris region comprising an iris pattern sufficiently distinct from the identified iris pattern to avoid identifying the subject within the image is determined and the identified iris region is replaced with the substitute iris region in the original image.
A method of estimating motion between a pair of image frames of a given scene comprises calculating respective integral images for each of the image frames and selecting at least one corresponding region of interest within each frame. For each region of interest, an integral image profile from each integral image is calculated, each profile comprising an array of elements, each element comprising a sum of pixel intensities from successive swaths of the region of interest for the frame. Integral image profiles are correlated to determine a relative displacement of the region of interest between the pair of frames. Each region of interest is divided into a plurality of further regions of interest before repeating until a required hierarchy of estimated motion for successively divided regions of interest is provided.
A computer-implemented method for viewing images on an interactive computing device comprises displaying an image from a stack comprising a display image and at least one compressed sub-image of nominally the same scene, each of the sub- images of the stack having been acquired at respective focal distances. Responsive to a user selecting a portion of the displayed image, the selected portion is mapped to a corresponding mapped portion of a sub-image within the stack according to the difference in focal distances between the displayed image and the sub-image. At least one row of compressed image blocks of the at least one sub-image extending across the mapped portion; and a reference value for a point in the compressed image stream of the sub-image preceding the row of compressed image blocks is determined. Using the reference, the row of blocks of the sub-image at least partially decoded, and a measure of focus for an area of the mapped portion coinciding with the decoded image blocks is computed to determine if at least that content of the sub-image should be displayed within a display image.
A hand-held digital camera has a touch-sensitive display screen ("touch screen") for image preview and user control of the camera, and a user-selectable panorama mode. Upon entering panorama mode the camera superimposes upon the touch screen a horizontal rectangular bar whose width and/or height are user-adjustable by interaction with the touch screen to select a desired horizontal sweep angle. After the sweep angle is set the camera automatically captures successive horizontally overlapping images during a sweep of the device through the selected sweep angle. Subsequently the camera synthesises a panoramic image from the successively captured images, the panoramic image having a width corresponding to the selected sweep angle.
A rearview imaging system for a vehicle (10) includes at least one video camera mounted at the rear of the vehicle for providing a wide angle horizontal field of view (FoV) rearwardly of the vehicle, and a display device in the vehicle at a position viewable by the driver. A video processor subdivides the camera FoV into three horizontally disposed sub-FOVs (RH FoV, Centre FoV, LH FoV) and displaying said sub-FoVs on visually separated side-by-side regions of the display device screen. The horizontal position and/or extent of at least one sub-FoV is variable as a function of the motion of the vehicle.
B60R 1/00 - Dispositions pour la visibilité optique; Dispositions de visualisation en temps réel pour les conducteurs ou les passagers utilisant des systèmes de capture d’images optiques, p.ex. des caméras ou des systèmes vidéo spécialement adaptés pour être utilisés dans ou sur des véhicules
42.
A METHOD AND SYSTEM FOR CORRECTING A DISTORTED INPUT IMAGE
A method for correcting a distorted input image comprises determining a local region of an image to be displayed and dividing said region into an array of rectangular tiles, each tile corresponding to a distorted tile with a non-rectangular boundary within said input image. For each tile of the local region, maximum and minimum memory address locations of successive rows of said input image sufficient to span said boundary of said distorted tile are determined. Successive rows of the distorted input from between said maximum and minimum addresses are read. Distortion of the non-rectangular portion of said distorted input image is corrected to provide a tile of a corrected output image which is stored.
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