Abstract: Systems and methods are provided for producing a stereo disparity map representing an imaged subject. A plurality of sensors (102 and 104) are operative to produce a plurality of images. Each image has an associated exposure according to an exposure level of an associated sensor. A system control (106) determines exposure levels for the plurality of sensors according to an exposure selection algorithm. A disparity processing component (112) is operative to generate a stereo disparity map from a plurality of images. An image merger (110) is operative to merge a plurality of images to produce a composite image having an increased dynamic range.

Abstract: Systems and methods are provided for identifying a position of a head of a vehicle occupant from a plurality of images of a vehicle interior. Image data is translated from the plurality of images to produce a virtual side view image of the vehicle interior (220). A largest grouping of pixels in the side view image having values within a desired range is identified (230). The grouping includes a plurality of pixel columns. A contour including uppermost pixels of each pixel column is produced and peaks are located within the contour (240, 250, and 260). The contour peaks are analyzed according to a heuristic voting algorithm to identify a peak location associated with the head of the vehicle occupant (270).

Abstract: Systems and methods are provided for constructing a classification architecture for a pattern recognition classifier that determines an associated occupant class of an occupant within a vehicle. A plurality of occupant classes are defined, with at least one of the occupant classes having an associated set of subclasses (202). A hierarchy of subclass partitions is determined based on a degree of similarity between subclasses associated with a given occupant class (210). Each successive partition in the hierarchy is an immediate partition of the preceding partition. The following is then performed iteratively until a termination event occurs. A subclass partition is selected according to the determined hierarchy (216/230). The fitness of a classifier model having an architecture derived from the selected subclass partition is evaluated (220).

Abstract: An image enhancing system (12) for a vehicle (10) comprises a display unit (14) for displaying modified images (38) and an imaging device (20) for receiving captured images (36) enhanced by the image enhancing system (12). The system (12) further includes an image enhancing module (26) in communication with the display unit (14) and the imaging device (20) such that pixels located in the captured images (36) are enhanced by repositioning the pixels from a first position to a second position via a transfer operation.

Abstract: A system (400) for classifying an input image into one of a plurality of output classes includes a plurality of pattern recognition classifiers (420, 422, 424). Each of the plurality of pattern recognition classifiers determines a candidate output class and at least one rejected output class for the input image from an associated subset of the plurality of output classes. Each classifier generates a confidence value associated with the classifier based on the determination. An arbitrator (430) selects a classifier having the best associated confidence value and eliminates the at least one rejected class determined at the selected classifier from consideration as the associated class for the input image.

Abstract: Systems and methods are provided for determining an associated occupant class for a vehicle occupant from an image of a vehicle interior. An image characterizer (154) determines a centroid of the image of the vehicle occupant is determined and produces an image representative signal that represents the image data as a series of discrete values according to its position relative to the determined centroid. A frequency domain transform (156) converts the image representative signal to a frequency domain to produce a plurality of coefficients. A pattern recognition classifier (56) determines an associated output class for the occupant utilizing at least two of the plurality of coefficients. A controller interface (58) regulates an actuatable occupant restraint device according to the determined output class.

Abstract: Systems and methods are provided for controlling a plurality of vehicle systems. A forward looking sensor (12) is configured to obtain a two-dimensional image of a space in front of the vehicle. A region identification element (14) divides the two-dimensional image into a plurality of regions. Each region represents a portion of the space forward of the vehicle. An image transform (16) transforms the two-dimensional image to a three-dimensional coordinate system representing the space in front of the vehicle to calculate depth information for at least a portion of the image. Each of a plurality of expert systems (18-20) have at least one associated region and control a vehicle system (22-24) according to data from their respective at least one associated region and the calculated depth information.

Abstract: System and methods are provided for classifying an occupant of a vehicle. An edge image generation component (102) produces an edge image of a vehicle occupant. A long term filtering component (104) filters across a plurality of edge images to produce a static edge image. A feature extraction component (106) extracts a plurality of features from the static edge image. A classification component (108) selects an occupant class for the vehicle occupant according to the extracted plurality of features.

Abstract: An apparatus (20) for determining a location of a person's head (90) includes stereo vision system (60) for imaging an area of interest such as the interior of a vehicle (26). The vision system provides an image signal of the area of interest. An analyzer (80) analyzes the image signal to identify head candidates (90?, 210, 212, 214, 216) in the area of interest and provides data regarding any identified head candidates in the area of interest. A processor (80) processes the provided data regarding identified head candidates to locate the person's head. In an air bag restraining system (22), a controller (50) monitors the location of the person's head and controls an air bag (34) in response to a sensed crash condition (52) and the location of the person's head.

Abstract: Systems and methods are provided for editing an image of a vehicle interior to isolate the occupant of a vehicle seat. An image generator (102) generates an image of a vehicle interior. A contour generator (104) produces a contour image from the generated image. A model selector (106) selects a contour model from a plurality of contour models according to the similarity of the contour model to a portion of the contour image. An image editor (108) removes a portion of the generated image representing at least a portion of the vehicle seat according to the selected contour model to produce an image of an occupant of the vehicle seat.

Abstract: Systems and methods are provided for identifying a position of a head of a vehicle occupant from a plurality of images of a vehicle interior. Image data is translated from the plurality of images to produce a virtual side view image of the vehicle interior. A largest grouping of pixels in the side view image having values within a desired range is identified. The grouping includes a plurality of pixel columns. A contour comprising uppermost pixels of each pixel column is produced and peaks are located within the contour. The contour peaks are analyzed according to a heuristic voting algorithm to identify a peak location associated with the head of the vehicle occupant.

Abstract: Systems and methods are provided for identifying a position of a head of a vehicle occupant from a plurality of images of a vehicle interior. Image data is translated from the plurality of images to produce a virtual side view image of the vehicle interior (162). A largest grouping of pixels in the side view image having values within a desired range is identified (164). The grouping includes a plurality of pixel columns. A contour including uppermost pixels of each pixel column is produced and peaks are located within the contour (166). The contour peaks are analyzed according to a heuristic voting algorithm to identify a peak location associated with the head of the vehicle occupant (172).

Abstract: Systems and methods are provided for constructing a classification architecture for a pattern recognition classifier that determines an associated occupant class of an occupant within a vehicle. A plurality of occupant classes are defined, with at least one of the occupant classes having an associated set of subclasses (202). A hierarchy of subclass partitions is determined based on a degree of similarity between subclasses associated with a given occupant class (210). Each successive partition in the hierarchy is an immediate partition of the preceding partition. The following is then performed iteratively until a termination event occurs. A subclass partition is selected according to the determined hierarchy (216/230). The fitness of a classifier model having an architecture derived from the selected subclass partition is evaluated (220).

Abstract: Systems and methods are provided for classifying an input feature vector, representing a vehicle occupant, into one of a plurality of occupant classes. A database (106) contains a plurality of feature vectors in a multidimensional feature space. Each feature vector has an associated class from the plurality of output classes. A data pruner (108) eliminates redundant feature vectors from the database. A data modeler (109) constructs an instance-based, non-parametric classification model (110) in the multidimensional feature space from the plurality of feature vectors. A class discriminator (112) selects an occupant class from the plurality of occupant classes according to the constructed classification model.

Abstract: Systems and methods are provided for generating training samples for a classification system associated with a vehicle occupant protection system. A three-dimensional virtual reality scene is generated (138) from a cockpit model having a set of at least two user configurable parameters (132) and an occupant model having a set of at least two user configurable parameters and a plurality of points of articulation (134). A plurality of training samples are generated from the virtual model (142). Each of the plurality of training samples has a first set of parameters associated with the cockpit model, a second set of parameters associated with the occupant model, and an occupant pose defined according to the points of articulation associated with the occupant model.

Abstract: Systems and methods are provided for detecting an occupant within a vehicle. An image of a vehicle interior, containing depth information for a plurality of image pixels, is generated at an image sensor (110). The vehicle interior is divided into at least one blob of contiguous pixels (160). The at least one blob is divided into a series of layers (170) wherein each successive layer represents a range of depth within the image. It is determined if the at least one blob represents an occupant according to at least one characteristic of the series of layers (190).

Abstract: Systems and methods are provided for identifying a position of a head of a vehicle occupant from a plurality of images of a vehicle interior. Image data is translated from the plurality of images to produce a virtual side view image of the vehicle interior. A largest grouping of pixels in the side view image having values within a desired range is identified. The grouping includes a plurality of pixel columns. A contour comprising uppermost pixels of each pixel column is produced and peaks are located within the contour. The contour peaks are analyzed according to a heuristic voting algorithm to identify a peak location associated with the head of the vehicle occupant.

Abstract: Systems and methods are provided for editing an image of a vehicle interior to isolate the occupant of a vehicle seat. An image generator (102) generates an image of a vehicle interior. A contour generator (104) produces a contour image from the generated image. A model selector (106) selects a contour model from a plurality of contour models according to the similarity of the contour model to a portion of the contour image. An image editor (108) removes a portion of the generated image representing at least a portion of the vehicle seat according to the selected contour model to produce an image of an occupant of the vehicle seat.

Abstract: Systems and methods are provided for producing a stereo disparity map representing an imaged subject. A plurality of sensors (102 and 104) are operative to produce a plurality of images. Each image has an associated exposure according to an exposure level of an associated sensor. A system control (106) determines exposure levels for the plurality of sensors according to an exposure selection algorithm. A disparity processing component (112) is operative to generate a stereo disparity map from a plurality of images. An image merger (110) is operative to merge a plurality of images to produce a composite image having an increased dynamic range.

Abstract: A method and apparatus (20) for recognizing and determining a location of an object (40) in an area of interest (31) comprises an imaging device (61) for obtaining an image of the area of interest. At least three identifying marks (104) are located at predetermined positions in the area of interest (31). The apparatus (20) also comprises a memory (78) in which the predetermined positions of the at least three identifying marks (104) are stored. A controller (80) determines whether the imaging device (61) is calibrated properly by analyzing the image obtained by the imaging device to determine whether positions of the at least three identifying marks (104) in the obtained image correspond to the predetermined positions stored in the memory (78). The controller (80) is also adapted to determine whether a view of the area of interest (31) from the imaging device (61) is obstructed.