Abstract: Technologies and techniques for vehicle perception. A first contour of a current image a dna second contour of a next image are determined relative to an optical center. The current image is scaled to the next image relative to the optical center, wherein the scaling includes applying a scale vector to the first contour. A frame offset vector is determined, and the second contour is translated, based on the frame offset vector and the scale vector, to align the translated second contour to a focus of expansion. An image velocity is determined, based on the first contour and the translated second contour, wherein the image velocity is used to determine object movement from the image data.

Abstract: Technologies and techniques for vehicle perception. Contours are extracted from image data, and a first and second contour of a current image and next image are determined along a plurality of image row boundaries, wherein the contours includes a plurality of contour points linked to each other via respective edges. An image velocity vector is applied to project each of the plurality of first contour points to the next image, wherein at least some of the projected first contour points are not located on an image row boundary. The projected contour points are processed to determine projected edges forming a projected link between each projected contour point. The projected contour points are moved along the projected link to align each of the moved projected contour points to a respective image boundary. Each of the moved projected contour points are then linked to each of the second contour points.

Abstract: Technologies and techniques for vehicle perception. Contours are extracted from image data, and a first and second contour of a current image and next image are determined along a plurality of image row boundaries, wherein the contours includes a plurality of contour points linked to each other via respective edges. An image velocity vector is applied to project each of the plurality of first contour points to the next image, wherein at least some of the projected first contour points are not located on an image row boundary. The projected contour points are processed to determine projected edges forming a projected link between each projected contour point. The projected contour points are moved along the projected link to align each of the moved projected contour points to a respective image boundary. Each of the moved projected contour points are then linked to each of the second contour points.

Abstract: Technologies and techniques for vehicle perception. A first contour of a current image a dna second contour of a next image are determined relative to an optical center. The current image is scaled to the next image relative to the optical center, wherein the scaling includes applying a scale vector to the first contour. A frame offset vector is determined, and the second contour is translated, based on the frame offset vector and the scale vector, to align the translated second contour to a focus of expansion. An image velocity is determined, based on the first contour and the translated second contour, wherein the image velocity is used to determine object movement from the image data.

Abstract: Technologies and techniques for vehicle perception. A contour extractor apparatus extracts contours from image data. Mapping offsets are determined between at least some of the grid points of a current image map and respective grid points of a next image map, and image velocity vectors are determined for at least some of mapping offsets. At least some of the grid points of the next image are warped to the respective grid points of the current image map. A determination is made if a contour of the warped grid points of the next image matches a contour of the respective grid points of the current map within a configured parameter. Object movement movement may then be determined from the image data, if the contour of the warped grid points of the next image matches the contour of the respective grid points of the current map within the configured parameter.

Abstract: A system, components, and methodologies are provided for image data processing and subsequent use to detect and/or identify objects and object movement in such image data to enable assistance, automation, control and/or documentation regarding transportation vehicle movement. An affine contour filter provides the ability to extract precise sub-pixel roots of contours that represent boundaries of blobs in an image that undergoes small affine changes such as translation, rotation and scale. Thereby lateral contour tracking may be performed wherein movement of an object may be tracked within the field of view of a camera by aligning the contours associated with the object in space-time. As a result, the size and shape of the object to be tracked need not be specified ahead of time.

Abstract: A system, components, and methodologies are provided for image data processing and subsequent use to detect and/or identify objects and object movement in such image data to enable assistance, automation, control and/or documentation regarding transportation vehicle movement. An affine contour filter provides the ability to extract precise sub-pixel roots of contours that represent boundaries of blobs in an image that undergoes small affine changes such as translation, rotation and scale. Thereby lateral contour tracking may be performed wherein movement of an object may be tracked within the field of view of a camera by aligning the contours associated with the object in space-time. As a result, the size and shape of the object to be tracked need not be specified ahead of time.

Abstract: A system and methodologies for neuromorphic (NM) vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking so as to detect and predict movement of a vehicle occupant.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking so as to detect and predict movement of a vehicle occupant.

Abstract: A system and methodologies for neuromorphic (NM) vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking so as to detect and predict movement of a vehicle occupant.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic (NM) vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.