Abstract: A method for multiview video data encoding is provided. The method includes: performing feature detection on first picture data relating to a first view to obtain a first set of features corresponding to said first view; generating a picture bitstream based on the first picture data relating to the first view; performing feature detection on second picture data relating to a second view to obtain a second set of features corresponding to said second view; performing feature matching of the first and second sets of features so as to identify an area of common characteristics; and performing prediction on second input picture data based on the area of common characteristics so as to generate a residual data bitstream.

Abstract: A method for multiview picture data encoding comprising the steps of: performing extraction of features from multiview picture data to obtain a plurality of feature maps; performing stitching and/or transforming of the obtained plurality of feature maps to obtain at least one panoramic map of features; performing transforming of the multiview picture data to select a plurality of patches of view of the multiview picture data; encoding the at least one panoramic map of features; and encoding the plurality of patches of view.

Abstract: Methods and devices for video data decoding and encoding are provided. The method for video data decoding includes: obtaining a picture bitstream; obtaining a feature bitstream indicating a residual set of features as a result of subtracting a second set of features detected in encoded picture data generated from original picture data by encoding from a first set of features detected in the original picture data; retrieving a decoded set of features from decoding the picture bitstream; and recovering the first set of features indicating the features detected in the input picture data from the decoded set of features and the residual set of features decoded from the feature bitstream.

Abstract: A visual feature processing method in an encoding device is disclosed. The visual feature processing method comprises: performing feature extraction from picture data to be encoded based on a predetermined feature extraction method to thereby obtain a set of extracted features; sorting the features in the set of extracted features based on a predetermined criterion; iteratively dividing the sorted set of extracted features in a plurality of subsets of features, said plurality of subsets of features comprising a first subset of features and at least one further subset of features, wherein the first subset of features is assigned a priority value which is higher than the priority value of the at least one further subset of features; and multiplexing the features of each subset of features for outputting for compressing, wherein the multiplexing is based on the priority value assigned to each subset of features.

Abstract: Computer-implemented methods, computer-readable media and devices for encoding video data using picture synthesis from features are provided. A computer-implemented method of encoding video data includes extracting features from a picture in a video; obtaining a predicted value of one or more regions in the picture by applying generative picture synthesis onto the features; obtaining a residual value of the one or more regions in the picture based on an original value of the one or more regions in the picture and the predicted picture; and encoding the residual value and the extracted features. Disclosed herein are also computer-implemented methods, computer-readable media and devices for decoding video data using picture synthesis from features.

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 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 method for analyzing behavior in an intelligent surveillance system, the system being operable to provide a series of consecutive images of an area under surveillance for consecutive time points, the method comprising the steps of: for each image of the series, generating a set of points defining at least one moving silhouette on an image; tracing the position of points in the sets of points on consecutive images in order to generate trajectories of points; providing a database of predefined trajectories corresponding to behavior; comparing the generated trajectories of points for said moving silhouette with database records; outputting information regarding the type of predefined behavior said moving silhouette corresponds to.

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.