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 system (400) for generating training images for a pattern recognition classifier (54) from three-dimensional image data representing an output class comprises a model constructor (404) that constructs an image model in a standard coordinate domain from the three-dimensional image data. A model transformer (406) manipulates the image model in the standard coordinate domain to produce at least one manipulated image model. An image restorer (408) maps the at least one manipulated image model from the standard coordinate domain to a coordinate domain associated with an image source utilized during the run-time operation of the pattern recognition classifier.

Abstract: An apparatus (100) for tracking at least one head candidate comprises an image analyzer (104) for analyzing an image signal to identify at least one of a possible plurality of new head candidates within an area of interest. The image analyzer (104) provides data regarding the identified head candidates. A tracking system (108) stores location information for at least one tracked head candidate. A candidate matcher (106) predicts the current position of a given tracked head candidate and selects a subset of the at least one of a plurality of new head candidates according to their distance from the predicted position. The similarity of each member of the selected subset to the tracked candidate is evaluated to determine if a member of the selected subset represents a current position of the tracked candidate.

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: A system for classifying image data includes a vision system (58) for continuously imaging an area (42) of interest and providing an image signals. A classifier (84) determines an image class corresponding to each image signal, determines a confidence level for each determined image class, determines a time period for the confidence level, and establishes an image classification in response thereto. Switching between image classifications is in response to the confidence level and time period of the confidence level. When used in a vehicle restraining system (20), other monitor vehicle parameters (54) can be used to adjust the confidence levels and time periods needed to switch between image classifications.

Abstract: A system (600) for classifying an input image into one of a plurality of output classes includes a plurality of pattern recognition classifiers (620, 622, 624). Each pattern recognition classifier is operative to process feature data associated with the input image to determine an associated output class of the input image. The system further includes a plurality of feature extractors (610, 612, 614). Each feature extractor extracts feature data from the input image for an associated one of the plurality of pattern recognition classifiers according to a classifier grid model representing the associated classifier.

Abstract: A system (600) for selectively generating training data for a pattern recognition classifier includes an image synthesizer (606) that combines a plurality of training images from an output class into a class composite image. A grid generator (608) generates a grid pattern representing the output class from the class composite image. A feature extractor (610) extracts feature data from the plurality of training images according to the generated grid pattern.

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.

Abstract: A method and apparatus (40) for testing an occupant position sensing system (12) of a vehicle (10) includes a motor (42) having a stationary portion (44) and a movable portion (46). A test object (90) is fixed relative to the movable portion (46) of the motor (42). A motor position sensor (64) senses a position of the movable portion (46) of the motor (42) relative to the stationary portion (44) and for providing a motor position signal indicative thereof. Motor drive electronics (58) are responsive to the motor position signal for controlling the motor (42) for moving the test object (90). A data recorder (80) is adapted to receive and record data from the occupant position sensing system (12) and is adapted to receive and record the motor position signal provided by the motor position sensor (64).

Abstract: A modified amalgam composition forming an adhesive bond with tooth structure treated with a dental adhesive. The modified amalgam can be prepared by admixing particulate additives into conventional amalgam alloy powder to form a modified alloy powder and then triturating the modified alloy powder with mercury. The modified amalgam when applied to a prepared tooth cavity that has been precoated with an acrylate- or methacrylate-functional dental adhesive results in an adhesive bond between the modified amalgam and coated tooth structure. Preferred particulate additives for the amalgam alloy powder are acrylate- or methacrylate-functional polymers, metal salts of acrylates or methacrylates, nonmetallic fillers, oxidizing agents and reducing agents.