Abstract: Methods and devices transform image data, which are transformed by a compression filter before being compressed and stored in a reference image memory. In an extension, an inverse transformation to that of the compression filter is performed by a decompression filter when image data from the reference memory are read out and decompressed. The methods and devices can be used for image compression methods and image decompression methods that use reference image memories.

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 reconstructed image is provided within the framework of predictive coding. The reconstructed image is compressed according to a coding mode of an image coding device and stored in a reference image memory.

Abstract: Multiple cameras are configured for use in video analytics. A single configuration tool is provided. The interrelationships between cameras are included within the configuration. Using a combination of text entry fields, registration of the cameras on a floor or other map, and marking on images from the cameras, an efficient workflow for configuration may be provided.

Abstract: A forensic video search user interface is disclosed that accesses databases of stored video event metadata from multiple camera streams and facilitates the workflow of search of complex global events that are composed of a number of simpler, low complexity events.

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: Object detection includes providing an image and determining at least one feature point. The at least one feature point defines a location of an image patch used for determining a feature descriptor, and the image patch defines an image area of the image. The feature descriptor is generated based on respective image intensities of a number of respective pairs of pixels with two dimensional coordinates located inside the image patch. An n-th component of the feature descriptor for an n-th pair of pixels is derived. A threshold is set depending on the number. The feature descriptor is generated by an arrangement of the M components. An indication signal is generated for a detected object when the feature descriptor is within a predefined distance to a reference feature descriptor.

Abstract: Annotation of a sequence of digitized images in multimedia data is aided by a computer analyzing the multimedia data to identify one or more objects and assigning each object to a respective role. The role assignment is determined by processing context information representing a model of the multimedia data.

Abstract: ANS method for transmitting data, in which basic data is transmitted while one or several packets are transmitted with data that complements the basic data and increases the quality of the basic data when being decoded by a receiver. The packets contain at least one field with information about how the complementing data of the respective packet increases the quality of the basic data. The field can be read independently of the complementing data of the respective packet. Based on the information, a decision can be made as to whether the packets are to be forwarded or decoded.

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: The disclosure relates to a method for encoding an XML-based document (DOC), where the contents of the document correspond to an XML-schema voice definition. According to one exemplary method, an encoded binary representation (BDOC) of the document is produced by associating the contents of the document with binary structural codes (SBC) using encoding tables (CT), textual contents of a “complex type” data type being associated with the “mixed” content model structural codes (SBC).

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: Second images coded in a coded output video stream are generated for the visual display of image contents of first images coded in multiple coded input video streams, such that first coded image data of the coded input video streams are copied into second coded image data of the coded output video stream.

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.

Abstract: A reconstructed image is provided within the framework of predictive coding. The reconstructed image is compressed according to a coding mode of an image coding device and stored in a reference image memory.