Abstract: A sparse motion field exchanges motion information between encoder and decoder. Side information indicates a suitable interpolation approach for interpolating the motion vectors of the dense motion field different from the signaled sparse motion field motion vectors. The side information is provided on a segment basis. The segments are derived at the encoder side and the decoder side similarly, based on the reference images and the sparse motion field.

Abstract: The present disclosure relates to an apparatus and a method for providing a plurality of motion vectors related to an image coded in a bitstream, comprising obtaining a set of sample positions within the image, obtaining respective motion vectors associated with the set of sample positions, deriving an additional motion vector based on information coded in the bitstream, determining an additional sample position located within a triangle, which is formed by three sample positions of the set of sample positions, based on the respective motion vectors associated with the three sample positions, the triangle not including any other sample position of the set, adding the additional sample position to the set of sample positions, and associating the derived additional motion vector with the additional sample position. Such method and apparatus provide for an efficient motion flow compression and reconstruction enabling to recover some sample positions without signaling them in the bitstream.

Abstract: Techniques are provided for sending and receiving digital video in high-quality compressed form over a network. Such techniques may include (a) performing chroma subsampling on an original video stream to yield an altered video stream; (b) applying video compression to the altered video stream to yield a compressed base layer (BL) stream; (c) creating an enhancement layer (EL) stream based on differences between the original video stream and a decompressed version of the BL stream, the EL stream including additional chroma information, which, when combined with the BL stream, encodes a video stream that has higher chroma fidelity to that of the original video stream than does the BL stream alone; and (d) sending both streams to a receiver device across the network to enable the receiver device to generate a version of the original video stream by combining the BL stream with the EL stream's additional chroma information.

Abstract: Techniques are provided for sending and receiving digital video in high-quality compressed form over a network. Such techniques may include (a) performing chroma subsampling on an original video stream to yield an altered video stream; (b) applying video compression to the altered video stream to yield a compressed base layer (BL) stream; (c) creating an enhancement layer (EL) stream based on differences between the original video stream and a decompressed version of the BL stream, the EL stream including additional chroma information, which, when combined with the BL stream, encodes a video stream that has higher chroma fidelity to that of the original video stream than does the BL stream alone; and (d) sending both streams to a receiver device across the network to enable the receiver device to generate a version of the original video stream by combining the BL stream with the EL stream's additional chroma information.

Abstract: In a method for coding a sequence of digital images, a prediction error between predicted values and the original values of pixels is processed for generating the coded sequence of digital images. A preset prediction mode is an intra-prediction mode based on pixels of a single image and includes, for a region of pixels with reconstructed values in the single image and for a template of an image area, comparing a first patch of pixels in the region that surround a first pixel to be predicted based on the template with several second patches. A predicted value of the first pixel is determined based on the values of one or more second pixels that have the highest similarity described by the similarity measure among all second pixels of the plurality of second pixels in the region.

Abstract: For each array of pixels, an autoregressive pixel-prediction method is performed based on a weighted sum of reconstructed pixel values of reconstructed pixels in a specific neighborhood region adjacent to the current pixel to be coded. For determining the weights, the pixel values in a specific training region adjacent to the current pixel are taken into account. The coding method is characterized by an appropriate determination of the specific neighborhood region and the specific training region in case that reconstructed pixel values do not exist for all pixels in the neighborhood region and the training region. In such a case, the number of pixels in the neighborhood region is reduced to a number of reconstructed pixels until the ratio between the number of pixels in the training region and the number of pixels in the neighborhood region exceeds a predetermined threshold.

Abstract: The embodiments relate to pixel-prediction methods and devices that are based on one of a selection of one out of at least two model functions that provide a prediction function and an adaptive model function that is capable to predict intensity characteristics of reference pixels used for prediction.

Abstract: For a compressed video stream formed of a sequence of compressed data packets, each compressed packet is assigned to a frame by processing the undecoded data packet. A frame includes packets. A first plurality of frames is assigned to a first sliding window and a second plurality of frames is assigned to a second sliding window. The first and second sliding windows have different frames. A first window indicator is calculated by determining a first indicator representing an average number of packets per frame within the first window, and/or a second indicator representing size information of the data within the first window. A second window indicator is calculated by determining a third indicator representing an average number of packets per frame within the second window, and/or a fourth indicator representing size information of the data within the second window. The first and the second window indicators are compared.

Abstract: A method for coding a sequence of digital images The invention refers to a method for coding a sequence of digital images (I), wherein the method uses a number of prediction modes for predicting values of pixels (P1) in the images (I) based on reconstructed values of pixels in image areas processed previously, where a prediction error (PE) between predicted values and the original values of pixels (P1) is processed for generating the coded sequence of digital images (CI). The invention is characterized in that a preset prediction mode is an intra-prediction mode based on pixels of a single image (I) and comprises steps i) and ii) as follows.

Abstract: A method identifies motion in an image sequence, which method involves an image processing device ascertaining a change of position of image features in a current image in respect of a reference image. In the method there is a paired association of corresponding image features, one of which can be found in the current image and one of which can be found in the reference image. Model parameters a determined, which describe the change of position for a motion model on the basis of the image features which are associated with one another. A static region is ascertained for the current image, in which static region the change of position of the image contents contained therein is smaller than a predetermined amount, and the model parameters are determined by using only image features which can be found outside the at least one static region.

Abstract: A method codes a sequence of digital images, each image having the same image format and including a number of pixels with assigned pixel values. Motion parameters between first and second images are determined, where based on said motion parameters a motion compensation is performed for coding the sequence of images, where said motion parameters are included in the coded sequence of images. The motion parameters between a first image and a second image include a scalar field having scalar values for a plurality of image positions in the image format. The scalar field is determined such that gradient vectors derived from the scalar field correspond to motion vectors for the motion compensation.

Abstract: The invention refers to a method for coding digital image data (I), the data comprising one or more arrays of pixels (p0, p112) with corresponding pixel values (i0, . . . , i112). For each array of pixels, an autoregressive pixel-prediction method is performed based on a weighted sum of reconstructed pixel values (i1, . . . , i12) of reconstructed pixels (p1, . . . , p12) in a specific neighborhood region (SN) adjacent to the current pixel (p0) to be coded. For determining the weights, the pixel values (p1, . . . , p12) in a specific training region (ST) adjacent to the current pixel (p0) are taken into account. The coding method is characterized by an appropriate determination of the specific neighborhood region (SN) and the specific training region (ST) in case that reconstructed pixel values do not exist for all pixels in the neighborhood region and the training region, e.g. at borders of the array of pixels.

Abstract: A method is provided for coding a sequence of digital images, wherein the method uses a number of prediction modes for predicting values of pixels in the images based on reconstructed values of pixels in image areas processed previously, where a prediction error between predicted values and the original values of pixels is processed for generating the coded sequence of digital images.

Abstract: A method for transmitting a vector having at least two vector components, each of the vector components described in a frequency. Each vector is represented as a bit number with a predetermined number of bit levels. The bit numbers are encoded according to a priority of the bit levels and the encoded bit numbers are transmitted.

Abstract: A method and system for automatic object detection and subsequent object tracking in accordance with the object shape in digital video systems having at least one camera for recording and transmitting video sequences. In accordance with the method and system, an object detection algorithm based on a Gaussian mixture model and expanded object tracking based on Mean-Shift are combined with each other in object detection. The object detection is expanded in accordance with a model of the background by improved removal of shadows, the binary mask generated in this way is used to create an asymmetric filter core, and then the actual algorithm for the shape-adaptive object tracking, expanded by a segmentation step for adapting the shape, is initialized, and therefore a determination at least of the object shape or object contour or the orientation of the object in space is made possible.

Abstract: The embodiments relate to pixel-prediction methods and devices that are based on one of a selection of one out of at least two model functions that provide a prediction function and an adaptive model function that is capable to predict intensity characteristics of reference pixels used for prediction.

Abstract: A method identifies motion in an image sequence, which method involves an image processing device ascertaining a change of position of image features in a current image in respect of a reference image. In the method there is a paired association of corresponding image features, one of which can be found in the current image and one of which can be found in the reference image. Model parameters a determined, which describe the change of position for a motion model on the basis of the image features which are associated with one another. A static region is ascertained for the current image, in which static region the change of position of the image contents contained therein is smaller than a predetermined amount, and the model parameters are determined by using only image features which can be found outside the at least one static region.

Abstract: A method codes a sequence of digital images, each image having the same image format and including a number of pixels with assigned pixel values. Motion parameters between first and second images are determined, where based on said motion parameters a motion compensation is performed for coding the sequence of images, where said motion parameters are included in the coded sequence of images. The motion parameters between a first image and a second image include a scalar field having scalar values for a plurality of image positions in the image format. The scalar field is determined such that gradient vectors derived from the scalar field correspond to motion vectors for the motion compensation.

Abstract: A prediction error (eq[x,y]) is added to a predicted frame ({circumflex over (f)}[x,y]) or a predicted block for receiving a decoded frame (gq[x,y]) or a decoded block to be further used in a prediction loop by an encoder or to be sent to the output of a decoder. The reference frame (gq[x,y]) or the reference block includes a useful signal part and a noise signal part. The reference frame (gq[x,y]) or reference block pass through a dedicated noise reducing filter to reduce or eliminate the noise signal part of the reference frame (gq[x,y]) or reference block.

Abstract: A coding method for the compression of an image sequence involves firstly determining a dense motion vector field for a current image region of the image sequence by comparison with at least one further image region of the image sequence. Furthermore, a confidence vector field is determined for the current image region. The confidence vector field specifies at least one confidence value for each motion vector of the motion vector field. Based on the motion vector field and the confidence vector field, motion vector field reconstruction parameters are then determined for the current image region. Furthermore, a decoding method decodes image data of an image sequence which were coded by such a coding method.