Abstract: A method, a device and a non-transitory computer-readable storage medium for setting a confidence threshold for objects detected in a region of a captured scene based on historical confidence scores for objects detected in that region.

Abstract: The present disclosure generally relates to a method for weighting of features in a feature vector of an object detected in a video stream capturing a scene, comprising: determining a feature vector comprising a set of features for a detected object in the video stream; acquiring a reference feature vector of a reference model of the scene; and assigning a weight to at least one feature of the determined feature vector, wherein the weight for a feature of the determined feature vector depends on a deviation measure indicative of a degree of deviation of the feature from a corresponding feature of the acquired reference feature vector of the reference model.

Abstract: A method for determining similarity in appearance of objects in image frames of a video sequence, comprises: processing first raw image data applying first image processing settings; detecting a first object; extracting first feature vectors; processing second raw image data applying second image processing settings; detecting a second object; extracting second feature vectors; determining the similarity of the first and second objects by comparing the first feature vectors to the second feature vectors; if the first feature vectors and the second feature vectors differ by more than a first threshold, and the first image processing settings differ from the second image processing settings by more than a second threshold: re-processing the first raw image data corresponding applying the second image processing settings; extracting, from the first image area, updated first feature vectors; comparing the updated first feature vectors to the one or more second feature vectors.

Abstract: A method for selecting a crop score threshold for enhancing tracking of objects in a scene captured in a video sequence is disclosed. A respective track is obtained for two different objects, each track comprising crops of object instances of the objects in in a video sequence, each crop having a crop score and a feature vector. Each track is split into respective more tracklets thereby forming four or more tracklets. For each candidate crop score threshold a respective difference between each tracklet and each other tracklet is determined based on differences between feature vectors of crops having a crop score above the candidate crop score threshold of each tracklet, and each other tracklet. A crop score threshold is selected from the set of crop score thresholds resulting in a maximum difference between the differences between tracklets of different tracks and the differences between tracklets of the same track.

Abstract: The present system and method generally relate to the field of camera surveillance, and in particular to object re-identification in video streams captured by a camera.

Abstract: A method of detecting a change of ratio of occlusion of a tracked object in a video sequence. For each of a plurality of image frames, a bounding box of the tracked object is determined and for each pair of successive image frames, an intersection over union (IoU) of a first bounding box in a first image frame and a second bounding box in a second image frame is calculated. Similarly, for a further pair of successive image frames, a further IoU of a first bounding box in a first image frame of the further pair of successive image frames and a second bounding box in a second image frame of the further pair of successive image frames is calculated. If the further IoU differs from the calculated IoUs by more than a threshold amount, the ratio of occlusion of the tracked object has changed.

Abstract: A method for selecting a crop score threshold for enhancing tracking of objects in a scene captured in a video sequence is disclosed. A respective track is obtained for two different objects, each track comprising crops of object instances of the objects in in a video sequence, each crop having a crop score and a feature vector. Each track is split into respective more tracklets thereby forming four or more tracklets. For each candidate crop score threshold a respective difference between each tracklet and each other tracklet is determined based on differences between feature vectors of crops having a crop score above the candidate crop score threshold of each tracklet, and each other tracklet. A crop score threshold is selected from the set of crop score thresholds resulting in a maximum difference between the differences between tracklets of different tracks and the differences between tracklets of the same track.

Abstract: A method, a device and a non-transitory computer-readable storage medium for setting a confidence threshold for objects detected in a region of a captured scene based on historical confidence scores for objects detected in that region.

Abstract: A method for tracking an object in a scene is provided, including receiving a first image frame of a first image stream capturing a scene; detecting or tracking a first object in the first image frame, and determining that the first object is in a first part of the first image frame; determining, using object detection, that the first object belongs to a first object class; determining, based on multiple values of a tracking parameter each specific for different parts of the first image frame and for different object classes, a first value of the tracking parameter for the first part of the first image and for the first object class, and tracking the first object in a second image frame of the first image stream subsequent to the first image frame, based on the first value of the tracking parameter.

Abstract: The present disclosure generally relates to a method for weighting of features in a feature vector of an object detected in a video stream capturing a scene, comprising: determining a feature vector comprising a set of features for a detected object in the video stream; acquiring a reference feature vector of a reference model of the scene; and assigning a weight to at least one feature of the determined feature vector, wherein the weight for a feature of the determined feature vector depends on a deviation measure indicative of a degree of deviation of the feature from a corresponding feature of the acquired reference feature vector of the reference model.

Abstract: A method of encoding a video stream comprising receiving a frame of a video stream to be encoded, performing motion detection in the frame to identify steady regions, and temporally filtering the frame so as to provide temporally filtered pixel values. For a pixel in the steady regions of the frame, the temporally filtered pixel value is used when encoding the pixel, on a condition that the pixel belongs to a block of pixels of the frame that will be intra-coded. On a condition that the pixel instead belongs to a block of pixels of the frame that will be inter-coded, a value that was used when encoding a corresponding pixel of the immediately preceding frame is used when encoding the pixel.

Abstract: An electronic device and a method for generating a high dynamic range (HDR) image frame. The method includes obtaining at least two digital image frames, where each of the at least two digital image frames is captured with a different exposure setting. The method includes generating, by a processor, a radiance map from the at least two digital image frames, and performing image fusion of the at least two digital image frames to generate a fused image. Further, the method includes combining, by the processor, color values of image channels of the fused image and the radiance map to generate the HDR image frame.

Abstract: A method of encoding a video stream comprising receiving a frame of a video stream to be encoded, performing motion detection in the frame to identify steady regions, and temporally filtering the frame so as to provide temporally filtered pixel values. For a pixel in the steady regions of the frame, the temporally filtered pixel value is used when encoding the pixel, on a condition that the pixel belongs to a block of pixels of the frame that will be intra-coded. On a condition that the pixel instead belongs to a block of pixels of the frame that will be inter-coded, a value that was used when encoding a corresponding pixel of the immediately preceding frame is used when encoding the pixel.

Abstract: An electronic device and a method for generating a high dynamic range (HDR) image frame. The method includes obtaining at least two digital image frames, where each of the at least two digital image frames is captured with a different exposure setting. The method includes generating, by a processor, a radiance map from the at least two digital image frames, and performing image fusion of the at least two digital image frames to generate a fused image. Further, the method includes combining, by the processor, color values of image channels of the fused image and the radiance map to generate the HDR image frame.