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 present disclosure can provide an image processing apparatus. In some embodiments, the image processing apparatus in accordance with the disclosure comprises memory configured to store a previously selected depth information value (dprev), (dprev; dprevi) having been selected for a previously processed fragment and signal processing logic (103).

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: A method for estimation of dimensions of an object present on images obtained from a set of N cameras and representing the same scene from different viewpoints, based on a 3D object model. The method comprises determining (302) a 3DMM model. It further comprises matching (303) the 3DMM model to each of N images of the set in order to determine a set of parameters hi, ?i, ?i, wherein hi describes the orientation of the matched model with respect to the i-th image; ?i describes the 3D shape of the model matched to the i-th image and ?i describes the appearance/texture of the model matched to the i-th image.

Abstract: A computer-implemented method for processing a distorted wide angle image with barrel distortion to obtain a plurality of reconstructed images, characterized in that it comprises the steps of: determining, on the basis of a mapping function representing the distortion of the distorted image, a reconstruction function representing the position of points (r0) of reconstructed image as a function of position of points (r1) on the distorted image, determining a plurality of viewing angles (?1, ?2, ?3), for each viewing angle (?1, ?2, ?3), generating a reconstructed image comprising points of the distorted image comprised within the particular viewing angle (?1, ?2, ?3) and reconstructed using the reconstruction function, such that each reconstructed image has its central point corresponding to the same point of the distorted image.

Abstract: A computer-implemented method for processing a distorted wide angle image with barrel distortion to obtain a plurality of reconstructed images, characterized in that it comprises the steps of: determining, on the basis of a mapping function representing the distortion of the distorted image, a reconstruction function representing the position of points (r0) of reconstructed image as a function of position of points (r1) on the distorted image, determining a plurality of viewing angles (?1, ?2, ?3), for each viewing angle (60 1, ?2, ?3), generating a reconstructed image comprising points of the distorted image comprised within the particular viewing angle (?1, ?2, ?3) and reconstructed using the reconstruction function, such that each reconstructed image has its central point corresponding to the same point of the distorted image.