Abstract: The disclosure relates to an image processing apparatus for selecting a plurality of depth information values for a subset of currently processed fragments of a set of currently processed fragments of a currently processed digital image. The image processing apparatus includes a non-transitory memory storage comprising instructions and one or more hardware processors in communication with the memory storage. The one or more hardware processors execute the instructions to: process the currently processed fragments of the set of currently processed fragments in parallel; and process the currently processed fragments of the subset of currently processed fragments in parallel.

Abstract: The disclosure relates to an image processing apparatus for selecting a plurality of depth information values for a subset of currently processed fragments of a set of currently processed fragments of a currently processed digital image. The image processing apparatus includes a non-transitory memory storage comprising instructions and one or more hardware processors in communication with the memory storage. The one or more hardware processors execute the instructions to: process the currently processed fragments of the set of currently processed fragments in parallel; and process the currently processed fragments of the subset of currently processed fragments in parallel.

Abstract: A method for video object tracking using stereoscopic images with depth maps. The method comprises calculating a first axis histogram for each depth map and applying: a first object detection method to track objects based on at least one of: the contents of the images and the depth maps; and a second object detection method to track objects based on the contents of the histograms of the depth maps. The locations of tracked objects are determined based on comparison of the results of the first object detection method and the second object detection method.

Abstract: A method for video object tracking, the method comprising the steps of: receiving a sequence of stereoscopic images; receiving a depth map for each stereoscopic image of the sequence; calculating a first axis histogram for each depth map; applying a first object detection method to track objects based on the contents of the images and/or the depth maps; applying, in parallel to the first object detection method a second object detection method to track objects based on the contents of the histograms of the depth maps; and determining locations of tracked objects based on comparison of the results of the first object detection method and second object detection method.

Abstract: An image coding method. The method includes encoding a first image, the first image having a reduced spatial resolution relative to an input image, wherein values of the first image depend on energy of corresponding areas of the input image, and encoding a first shape information of the shape of a spatial spectrum of the input image. The method further includes reconstructing a second image from the encoded first image, reconstructing a second shape information from the encoded first shape information, and generating a noise image having an intensity described by the second image and having a spectrum shape described by the second shape information.

Abstract: A computer-implemented method for video signal encoding with motion estimation, the video signal comprising frames divided into prediction units, the method comprising the steps of: determining (401) the current prediction unit (PUX) to be encoded, creating (407) a list (LMVXpred) comprising motion vector predictions (MVPUY) from neighboring units (PUY), selecting (411) from the list (LMVXpred) the motion vector prediction which is the best according to a predetermined cost function for encoding the current prediction unit (PUX), using (412) the selected prediction number to encode the current prediction unit (PUX).