Abstract: An image encoding/decoding method and apparatus are provided. The image decoding method includes obtaining, from a bitstream, network abstraction layer (NAL) unit type information of at least one NAL unit including coded image data, determining at least one NAL unit type of one or more slices in the current picture based on the obtained NAL unit type information, and decoding the current picture based on the determined NAL unit type. The current picture is determined to be a random access skipped leading (RASL) picture, based on the determined NAL unit type including a RASL picture NAL unit type (RASL_NUT). When an intra random access point (IRAP) picture associated with the RASL picture is a first picture in decoding order, the RASL picture is decoded, based on the RASL picture including one or more slices having a random access decodable leading (RADL) picture NAL unit type (RADL_NUT).

Abstract: A method and an apparatus for processing a three-dimensional video, a readable storage medium and an electronic device are involved in the present disclosure, and the present disclosure relates to the field of electronic information technologies. The method is applied to a terminal device, and includes: sending an initial two-dimensional image to a server, so that the server generates an initial three-dimensional video according to the initial two-dimensional image; receiving the initial three-dimensional video sent by the server, and processing the initial three-dimensional video to obtain a target three-dimensional video. According to the present disclosure, a two-dimensional image on the terminal device is uploaded to the server and is converted into a three-dimensional video by the server, then the three-dimensional video is processed by the terminal device.

Abstract: The various embodiments of the invention relates to a method and a technical equipment for video compression. The method comprises processing volumetric image data comprising a plurality of points; defining a hemisphere (601) around a surface (602) normal at each point in the volumetric image; partitioning each of the defined hemispheres spatially into a predefined number of angles (603); determining a representative radiance value for each angle of the predefined number of angles (603) of a defined hemisphere (601); generating a matrix (610) for a point storing the determined representative radiance values; and encoding the generated matrix (610) for the point for video compression.

Abstract: A video coding mechanism is disclosed. The mechanism includes receiving a bitstream including a first slice of a coded image. The coded image is associated with a picture parameter set (PPS) in the bitstream. The first slice is associated with a slice header in the bitstream. A list of identifiers (IDs) is parsed from the PPS. A first ID is parsed from the slice header of the first slice. The first ID matches one of the IDs in the list of IDs in the PPS. A list of tiles coded in the first slice is determined based on the first ID. The first slice is determined to generate a reconstructed sub-image of the coded image.

Abstract: Aspects of the disclosure provide methods, apparatuses, and non-transitory computer-readable storage mediums for video encoding/decoding. In a method, a current block is determined to be a parent node of a local partition tree structure. A tree depth of the local partition tree structure is less than or equal to a threshold. Then the current block is partitioned according to the local partition tree structure. The current block is reconstructed based on a prediction mode of the current block. In another method, chroma samples of the current block are partitioned into sub-blocks. The chroma samples of one sub-block are predicted based on a subset of chroma intra prediction modes including planar, DC, horizontal, vertical, DM, L_CCLM, T_CCLM, and LT_CCLM. Then the current block is reconstructed based on the predicted chroma samples.

Abstract: A distributed video management system for video surveillance that allows for monitoring a camera allocation parameter and dynamic reallocation of video cameras to available camera nodes in response to detecting a change in the allocation parameter. As such, the system may provide for load balancing of the processing of video data from the video cameras with reference to the allocation parameter. The change in allocation parameter may be due to a number of potential contexts, including a change in availability of camera nodes, a change in the nature of the video data captured, a change in computational load, or other change that results in a change in allocation parameter. The allocation parameter may be continually monitored to allocate video cameras to camera nodes in the system for enhanced system performance in view of potentially changing conditions.