Abstract: Systems and methods are provided for imaging a region of interest. A structured light source is configured to provide a substantially two-dimensional light curtain within a field of view of the camera formed by at least one projected laser beam at a wavelength detectable by the camera. An image analysis component is configured to detect objects within the region of interest from at least a position of the at least one projected laser beam within the image.

Abstract: Systems and methods are provided for imaging a region of interest. A structured light source is configured to provide a substantially two-dimensional light curtain within a field of view of the camera formed by at least one projected laser beam at a wavelength detectable by the camera. An image analysis component is configured to detect objects within the region of interest from at least a position of the at least one projected laser beam within the image.

Abstract: An image of a visual scene, comprising a plurality of pixels. is acquired and an associated range map is either determined therefrom or separately acquired. Elements of the range map comprise distances from the camera for each pixel of the image. In one aspect, either the image or the range map is processed with a connected-components sieve filter that locates clusters of pixels or elements that are connected to one another along either adjacent rows, columns or diagonally. In another aspect, a cross-range value of range-map element is compared with a down-range-responsive cross-range threshold of a boundary of a collision-possible space and the pixel or element is nulled or ignored if associated with a location that is not in the collision-possible space. The collision-possible space is responsive to an operating condition of a vehicle from which the image is acquired.

Abstract: A driver alertness detection system includes an imaging unit configured to image an area in a vehicle compartment where a driver's head is located; an image processing unit configured to receive the image from the imaging unit, and to determine positions of the driver's head and eyes; and a warning unit configured to determine, based on the determined position of the driver's head and eyes as output by the image processing unit, whether the driver is in an alert state or a non-alert state, and to output a warning to the driver when the driver is determined to be in the non-alert state.

Abstract: An image of a visual scene, comprising a plurality of pixels. is acquired and an associated range map is either determined therefrom or separately acquired. Elements of the range map comprise distances from the camera for each pixel of the image. In one aspect, either the image or the range map is processed with a connected-components sieve filter that locates clusters of pixels or elements that are connected to one another along either adjacent rows, columns or diagonally. In another aspect, a cross-range value of range-map element is compared with a down-range-responsive cross-range threshold of a boundary of a collision-possible space and the pixel or element is nulled or ignored if associated with a location that is not in the collision-possible space. The collision-possible space is responsive to an operating condition of a vehicle from which the image is acquired.

Abstract: A profile of an object is extracted from an image of a visual scene and a center of the profile is then determined. A measurement vector is determined comprising a plurality of distances to the profile from the center, at a plurality of angles relative to and through the center. The measurement vector is filtered with a central moving average filter, and then compared with at least one stored vector representative of at least one type of reference object, wherein the central moving average filter is responsive to the type of the at least one type of reference object, responsive to which a determination is made as to whether or not the object corresponds to at least one reference object, so as to provide for identifying the object in the visual scene.

Abstract: A range map of a visual scene generated by a stereo vision and associate image processing system, and is filtered to remove objects beyond a region of interest and for which a collision is not possible, and to remove an associated road surface. Objects clustered in range bins are separated by segmentation. A composite range map is generated using principale components analysis and processed with a connected-components sieve filter. Objects are identified using one or more of a harmonic profile and other features using an object recognition processor using a combination of inclusive, exclusive and harmonic networks to generate a classification metric.

Abstract: A plurality of features determined from at least a portion of an image containing information about an object are processed with an inclusive neural network, and with a plurality of exclusive neural networks, so as to provide a plurality of inclusive probability values representing probabilities that the portion of the image corresponds to at least one of at least two different classes of objects, and for each exclusive neural network, so as to provide first and second exclusive probability values representing probabilities that the portion of the image respectively corresponds. or not. to at least one class of objects. The plurality of inclusive probability values, and the first and second exclusive probability values from each of the exclusive neural networks, provide for identifying whether the portion of the image corresponds, or not, to any of the at least two different classes of objects.

Abstract: A driver alertness detection system includes an imaging unit configured to image an area in a vehicle compartment where a driver's head is located; an image processing unit configured to receive the image from the imaging unit, and to determine positions of the driver's head and eyes; and a warning unit configured to determine, based on the determined position of the driver's head and eyes as output by the image processing unit, whether the driver is in an alert state or a non-alert state, and to output a warning to the driver when the driver is determined to be in the non-alert state.

Abstract: A plurality of features determined from at least a portion of an image containing information about an object are processed with an inclusive neural network, and with a plurality of exclusive neural networks, so as to provide a plurality of inclusive probability values representing probabilities that the portion of the image corresponds to at least one of at least two different classes of objects, and for each exclusive neural network, so as to provide first and second exclusive probability values representing probabilities that the portion of the image respectively corresponds. or not. to at least one class of objects. The plurality of inclusive probability values, and the first and second exclusive probability values from each of the exclusive neural networks, provide for identifying whether the portion of the image corresponds, or not, to any of the at least two different classes of objects.

Abstract: A range map of a visual scene generated by a stereo vision and associate image processing system, and is filtered to remove objects beyond a region of interest and for which a collision is not possible, and to remove an associated road surface. Objects clustered in range bins are separated by segmentation. A composite range map is generated using principle components analysis and processed with a connected components sieve filter. Objects are identified using one or more of a harmonic profile and other features using an object recognition processor using a combination of inclusive, exclusive and harmonic networks to generate a classification metric.

Abstract: A camera (32) captures successive images of light stripes (22) projected onto an object by a light curtain (18) positioned by a light source positioner (28). A background image is subtracted (616) therefrom, and the resulting image is boosted by binning (618), binarized with a thresholding algorithm (620), skeletonized (622), interpolated (624) and stored (626). Interpolated images are acquired for a plurality of light stripes (22). A processor (30) generates (1604) a 3-D surface model from Cartesian coordinates computed for non-zero camera pixels. A volumetric representation is determined (1610) from the offset of the object surface model relative to a model of a proximate surface, e.g. a seating surface (24). The object is classified (1614), e.g. by a trainable pattern recognitions system, responsive to 3-D shape descriptors (1606) of the 3-D surface model and to the volumetric representation (1610) or portions (1612) thereof.

Abstract: An eye-safe light curtain is generated by a plurality of LED's illuminating a cylindrical lens having a corrugated cylindrical surface. A camera generates a first image of an avoidance zone boundary of an air bag inflator with the light curtain off, and a second image of with the light curtain on along the avoidance zone boundary. The first image is subtracted from the second image, and the resulting difference image is binned to enhance signal strength. A penetration of the avoidance zone is classified from features of the leading edge of the binned image, and the air bag inflator is disabled if the avoidance zone is penetrated by an occupant at risk of injury from the deployment thereof. An image of the light curtain may be recovered for high ambient lighting conditions by adapting the exposure time of the camera responsive to the percentage of pixels in a mask region of the first image having values exceeding a threshold.