Abstract: A method of identifying, with a camera, an object in an image of a scene, by determining the distinctiveness of each of a number of attributes of an object of interest, independent of the camera viewpoint, determining the detectability of each of the attributes based on the relative orientation of a candidate object in the image of the scene, determining a camera setting for viewing the candidate object based on the distinctiveness of an attribute, so as to increase the detectability of the attribute, and capturing an image of the candidate object with the camera setting to determine the confidence that the candidate object is the object of interest.

Abstract: A method of determining a lowest point of a target object in an image of a scene. A region of the target object in the image is received. A horizontal vanishing line of the image is received. At least one reference object in the scene is selected. At least a first line connecting the received region of the target object and a highest point of the reference object is determined. At least an intersection point of the first line and the horizontal vanishing line is determined. At least a second line connecting the determined intersection point to a lowest point of the reference object is determined; and a lowest point of the target object is determined based on the second line.

Abstract: A method of matching a person in captured images comprises determining first feature vectors from a first image sequence of person(s), and determining second feature vectors from a second image sequence of person(s). The first and second feature vectors are determined based on properties of pixels located in the first and second image sequences respectively. The method further comprises, for a first feature vector corresponding to a first person in the first image sequence, determining a reference distance to one of the second feature vectors corresponding to a reference person in the second image sequence; determining a distance metric by constraining a distance between the first feature vector and a feature vector corresponding to the first person in the second image sequence, according to the determined reference distance; and matching a pair of images of the person in the captured images based on the distance metric.

Abstract: A method of determining a lowest point of a target object in an image of a scene. A region of the target object in the image is received. A horizontal vanishing line of the image is received. At least one reference object in the scene is selected. At least a first line connecting the received region of the target object and a highest point of the reference object is determined. At least an intersection point of the first line and the horizontal vanishing line is determined. At least a second line connecting the determined intersection point to a lowest point of the reference object is determined; and a lowest point of the target object is determined based on the second line.

Abstract: A method of identifying, with a camera, an object in an image of a scene, by determining the distinctiveness of each of a number of attributes of an object of interest, independent of the camera viewpoint, determining the detectability of each of the attributes based on the relative orientation of a candidate object in the image of the scene, determining a camera setting for viewing the candidate object based on the distinctiveness of an attribute, so as to increase the detectability of the attribute, and capturing an image of the candidate object with the camera setting to determine the confidence that the candidate object is the object of interest.

Abstract: A method of identifying, with a camera, an object in an image of a scene, by determining the distinctiveness of each of a number of attributes of an object of interest, independent of the camera viewpoint, determining the detectability of each of the attributes based on the relative orientation of a candidate object in the image of the scene, determining a camera setting for viewing the candidate object based on the distinctiveness of an attribute, so as to increase the detectability of the attribute, and capturing an image of the candidate object with the camera setting to determine the confidence that the candidate object is the object of interest.

Abstract: A method of determining a property of an image (176) captured by a camera (127). Vanishing points (320, 330, 340) are in the image (176). Each pixel of the image (176) is associated with one or more of the vanishing points (320, 330, 340) based on an orientation of the image gradient at the pixel. The image is partitioned into a set of regions associated with a pair of the determined vanishing points based on the vanishing point associations for pixels in the image (176). Boundaries of the regions are aligned with the associated vanishing points. For at least one of the plurality of regions, a confidence value is determined for the property of the image based on pixels in the region. The property of the image is determined for one or more pixels within the image (176) based on the confidence value.

Abstract: Disclosed is a method of determining a 3D trajectory of an object from at least two observed trajectories of the object in a scene. The observed trajectories are captured in a series of images by at least one camera, each of the images in the series being associated with a pose of the camera. First and second points of the object from separate parallel planes of the scene are selected. A first set of 2D capture locations corresponding to the first point and a second set of 2D capture locations corresponding to the second point are reconstructed to determine an approximated 3D trajectory of the object.

Abstract: A method of detecting a supporting surface region in an image captured by a camera is disclosed. An object in the image is detected. One or more regions of the image in which a lower part of the detected object exists are determined. A degree of confidence for each of the regions is determined. The degree of confidence indicates likelihood of a corresponding region being a supporting surface region. One or more of the regions are selected based on each corresponding degree of confidence. Similarity of other regions in the image to at least one of the selected regions is determined. The supporting surface region is detected based on the determined similarity.

Abstract: A method of identifying, with a camera, an object in an image of a scene, by determining the distinctiveness of each of a number of attributes of an object of interest, independent of the camera viewpoint, determining the detectability of each of the attributes based on the relative orientation of a candidate object in the image of the scene, determining a camera setting for viewing the candidate object based on the distinctiveness of an attribute, so as to increase the detectability of the attribute, and capturing an image of the candidate object with the camera setting to determine the confidence that the candidate object is the object of interest.

Abstract: A method of determining a boundary of an obstacle which occludes an object in an image, is disclosed. At least one object in the image and a further image captured by a camera is determined. A plurality of regions in which the at least one object is detected, is determined from the images. Locations of edges of the plurality of regions are determined A common location is determined from the determined edges. The boundary of the obstacle is determined, where the boundary comprises a part of the edges at the common location.

Abstract: A method of determining a property of an image (176) captured by a camera (127), is disclosed. Vanishing points (320, 330, 340) in the image (176). Each pixel of the image (176) is associated with one or more of the vanishing points (320, 330, 340) based on an orientation of the image gradient at the pixel. The image is partitioned into a set of regions associated with a pair of the determined vanishing points based on the vanishing point associations for pixels in the image (176). Boundaries of the regions are aligned with the associated vanishing points. For at least one of the plurality of regions, a confidence value is determined for the property of the image based on pixels in the region. The property of the image is determined for one or more pixels within the image (176) based on the confidence value.

Abstract: A method of determining a boundary of an obstacle which occludes an object in an image, is disclosed. At least one object in the image and a further image captured by a camera is determined. A plurality of regions in which the at least one object is detected, is determined from the images. Locations of edges of the plurality of regions are determined A common location is determined from the determined edges. The boundary of the obstacle is determined, where the boundary comprises a part of the edges at the common location.

Abstract: A method of detecting a supporting surface region in an image captured by a camera is disclosed. An object in the image is detected. One or more regions of the image in which a lower part of the detected object exists are determined. A degree of confidence for each of the regions is determined. The degree of confidence indicates likelihood of a corresponding region being a supporting surface region. One or more of the regions are selected based on each corresponding degree of confidence. Similarity of other regions in the image to at least one of the selected regions is determined. The supporting surface region is detected based on the determined similarity.