Abstract:
A method for encoding digital images or video streams, comprises: - a receiving phase, wherein a portion of an image (f) is received; - a graph weights prediction (GWP) phase, wherein the elements of a weights matrix (W) associated to the graph related to the blocks of the image (predicted blocks) are predicted on the basis of reconstructed, de-quantized and inverse-transformed pixel values of at least one previously coded block (predictor block) of the image (f), the weights matrix (W) being a matrix comprising elements (wij) denoting the level of similarity between a pair of pixels composing said image (f), - a graph transform computation phase, wherein the graph Fourier transform of the blocks of the image (f) is performed, obtaining for said blocks a set of coefficients determined on the basis of the predicted weights; - a coefficients quantization phase, wherein said coefficients are quantized - an output phase wherein a bitstream comprising said transformed and quantized coefficients is transmitted and/or stored.
Abstract:
A method is described for generating a three-dimensional video stream by starting from a sequence of video images, said sequence comprising a first view (V 0 ), at least one second view (V i ) of a scene, as well as a depth map (D 0 ) of said first view (V o ), or a disparity map of said at least one second view (V 1 ) with respect to the first view (V 0 ), the method comprising, for one image, the following steps: obtaining at least one occlusion image (O 1 ) comprising the occluded pixels of said second view (V 1 ) by starting from said depth map (D 0 ) or from said disparity map; generating a compacted occlusion image (OC 1 ) by spatially repositioning said occluded pixels of said at least one occlusion image (O 1 ), so as to move said pixels closer to one another; said three-dimensional video stream comprising, for one image, said first view (V 0 ), said depth map (D 0 ), or said disparity map, and said at least one compacted occlusion image (OC 1 ).
Abstract:
The present invention relates to a method for pruning a neural network (100) comprising a plurality of neurons (105), said method comprising:- an initialization phase, wherein input information is fetched comprising at least parameters ({wni,bni}) related to said neural network (100) and a dataset (D) representative of a task that said neural network (100) has to deal with, wherein said parameters ({wni,bni}) comprising a weights vector (wni) and/or a bias (bni) related to at least one neuron (105) of said plurality of neurons;- a regularization phase, wherein said neural network (100) is trained according to a training algorithm by using said dataset (D);- a thresholding phase, wherein an element (wnij) of said weights vector (wni) is put at zero when its absolute value is below a given threshold (T),said method wherein, during said regularization phase, said parameters ({wni,bni}) evolve according to a regularized update rule based on a neural sensitivity measure (S) to drive towards zero parameters related to at least one less sensitive neuron (108) of said neural network (100), wherein said neural sensitivity measure (S) is based on a pre-activation signal of at least one neuron (105) of said plurality of neurons.
Abstract:
The present invention relates to a method for encoding the borders of pixel regions of an image, wherein the borders contain a sequence of vertices subdividing the image into regions of pixels (superpixels), by generating a sequence of symbols from an alphabet comprising the step of: - defining for each superpixel a first vertex for coding the borders of the superpixel according to a criterion common to all superpixels; - defining for each superpixel the same coding order of the border vertices, either clockwise or counter-clockwise; - defining the order for coding the superpixels on the base of a common rule depending on the relative positions of the first vertices; - defining a set of vertices as a known border ( Γ ), wherein the following steps are performed for selecting a symbol of the alphabet, for encoding the borders of the superpixels: a) determining the first vertex of the next superpixel border individuated by the common criterion; b) determining the next vertex to be encoded on the basis of the coding direction; c) selecting a first symbol ("0") for encoding the next vertex if the next vertex of a border pertains to the known border ( Γ ), d) selecting a symbol ("1"; "2") different from the first symbol ("0") if the next vertex is not in the known border (( Γ ); e) repeating steps b), c), d) and e) until all vertices of the superpixel border have been encoded; f) adding each vertex of the superpixel border that was not in the known border ( Γ ) to the set (( Γ ); g) determining the next superpixel whose border is to be encoded according to the common rule, if any; i) repeating steps a)-g) until the borders of all the superpixels of the image have being added to the known border ( Γ ).
Abstract:
The present invention relates to an apparatus and a method for image segmentation, which comprises a pre-segmentation phase (P1), wherein a set of points of said image is selected, a morphological expansion phase (P3), wherein the set of points selected during the pre-segmentation phase (P1) is expanded by taking into account the spatial distribution of the points of the selected set in the image, a graph generation phase (SP41), wherein a graph (GR) is generated on the basis of the image and the selected set of points, a graph partitioning phase (SP42), wherein a set of nodes of the graph (GR) is selected on the basis of the characteristics of said graph (GR) and the points corresponding to the selected nodes are added to the selected set of points.
Abstract:
The present invention relates to an apparatus and a method for image segmentation, which comprises a pre-segmentation phase (P1), wherein a set of points of said image is selected, a morphological expansion phase (P3), wherein the set of points selected during the pre-segmentation phase (P1) is expanded by taking into account the spatial distribution of the points of the selected set in the image, a graph generation phase (SP41), wherein a graph (GR) is generated on the basis of the image and the selected set of points, a graph partitioning phase (SP42), wherein a set of nodes of the graph (GR) is selected on the basis of the characteristics of said graph (GR) and the points corresponding to the selected nodes are added to the selected set of points.
Abstract:
The present invention relates to an apparatus and a method for image segmentation, which comprises a pre-segmentation phase (P1), wherein a set of points of said image is selected, a morphological expansion phase (P3), wherein the set of points selected during the pre-segmentation phase (P1) is expanded by taking into account the spatial distribution of the points of the selected set in the image, a graph generation phase (SP41), wherein a graph (GR) is generated on the basis of the image and the selected set of points, a graph partitioning phase (SP42), wherein a set of nodes of the graph (GR) is selected on the basis of the characteristics of said graph (GR) and the points corresponding to the selected nodes are added to the selected set of points.