Abstract:
In one example, a device for decoding video data includes a video decoder configured to decode one or more syntax elements of a current reference picture set (RPS) prediction data structure, wherein at least one of the syntax elements represents a picture order count (POC) difference between a POC value associated with the current RPS and a POC value associated with a previously decoded RPS, form a current RPS based at least in part on the RPS prediction data structure and the previously decoded RPS, and decode one or more pictures using the current RPS. A video encoder may be configured to perform a substantially similar process during video encoding.
Abstract:
A video encoder signals, in a bitstream, a syntax element that indicates whether a current video unit is predicted from a VSP picture. The current video unit is a macroblock or a macroblock partition. The video encoder determines, based at least in part on whether the current video unit is predicted from the VSP picture, whether to signal, in the bitstream, motion information for the current video unit. A video decoder decodes the syntax element from the bitstream and determines, based at least in part on the syntax element, whether the bitstream includes the motion information.
Abstract:
In one example, a device includes a video coder configured to code a picture order count (POC) value for a first picture of video data, code a second-dimension picture identifier for the first picture, and code, in accordance with a base video coding specification or an extension to the base video coding specification, a second picture based at least in part on the POC value and the second-dimension picture identifier of the first picture. The video coder may comprise a video encoder or a video decoder. The second-dimension picture identifier may comprise, for example, a view identifier, a view order index, a layer identifier, or other such identifier. The video coder may code the POC value and the second-dimension picture identifier during coding of a motion vector for a block of the second picture, e.g., during advanced motion vector prediction or merge mode coding.
Abstract:
Techniques are described for determining a disparity vector for a current block based on disparity motion vectors of one or more spatially and temporally neighboring regions to a current block to be predicted. The spatially and temporally neighboring regions include one or a plurality of blocks, and the disparity motion vector represents a single vector in one reference picture list for the plurality of blocks within the spatially or temporally neighboring region. The determined disparity vector could be used to coding tools which utilize the information between different views such as merge mode, advanced motion vector prediction (AMVP) mode, inter-view motion prediction, and inter-view residual prediction.
Abstract:
Provided are systems, methods, and computer-readable medium for maintaining blob trackers for video frames. The techniques and systems described herein identify a candidate sleeping tracker that is a false positive. In some examples, a false positive candidate sleeping tracker can be identified when an object associated with the candidate sleeping tracker was split from a previous object, and the object is within a target sleeping bounding region for the candidate sleeping tracker. The tracker for the object can be assigned a state that indicates that the blob will not continue to be tracked when the blob is detected as background. In some examples, a false positive candidate sleeping tracker can be identified when a maturity or age for the candidate sleeping tracker in insufficient.
Abstract:
Provided are methods, apparatus, and computer-readable mediums for tracking objects that intersect with an exclusion zone defined for a scene being captured by a video camera. An exclusion zone can delineate an area of a video frame where background objects may be moving. The exclusion zone informs an object tracking system that objects within the exclusion zone should not be tracked. In various implementations, the object tracking system can determine that a bounding box for a blob intersects with the exclusion zone. The object tracking system can further, based on the bounding box intersecting with the exclusion zone, prevent outputting of a blob tracker associated with the blob.
Abstract:
Techniques and systems are provided for tracking objects in one or more video frames. For example, a candidate bounding box for an object tracker can be obtained based on an application of an object detector to at least one key frame in the one or more video frames, the candidate bounding box being associated with one or more input attributes. A set of metrics indicating a degree of change of one or more physical attributes of the object can also be determined. Based on the set of metrics, it can be determined whether to post-process the input attributes to generate one or more output attributes of a current output bounding box. An object can be tracked in a current frame using the current output bounding box.
Abstract:
Techniques and systems are provided for classifying objects in one or more video frames. For example, one or more bounding regions are determined for a current video frame of a scene. The one or bounding regions are determined based on object tracking performed for one or more blobs detected for the current video frame. The one or more bounding regions are associated with the one or more blobs. A blob includes pixels of at least a portion of one or more objects in the current video frame. One or more regions of interest are determined in the current video frame of the scene. The one or more regions of interest are determined using the one or more bounding regions determined for the current video frame. One or more objects within the one or more regions of interest are classified using a trained network applied to the one or more regions of interest.
Abstract:
Techniques and systems are provided for maintaining blob trackers for one or more video frames. For example, a blob tracker can be identified for a current video frame. The blob tracker is associated with a blob detected for the current video frame, and the blob includes pixels of at least a portion of one or more objects in the current video frame. One or more characteristics of the blob tracker are determined. The one or more characteristics are based on a bounding region history of the blob tracker. A confidence value is determined for the blob tracker based on the determined one or more characteristics, and a status of the blob tracker is determined based on the determined confidence value. The status of the blob tracker indicates whether to maintain the blob tracker for the one or more video frames. For example, the determined status can include a first type of blob tracker that is output as an identified blob tracker-blob pair, a second type of blob tracker that is maintained for further analysis, or a third type of blob tracker that is removed from a plurality of blob trackers maintained for the one or more video frames.
Abstract:
A video coder may perform a simplified depth coding (SDC) mode, including simplified residual coding, to code a depth block according to any of a variety of, e.g., at least three, depth intra prediction modes. For example, the video coder may perform the SDC mode for coding a depth block according to depth modeling mode (DMM) 3, DMM 4, or a region boundary chain coding mode. In such examples, the video coder may partition the depth block, and code respective DC residual values for each partition. In some examples, the video coder may perform the SDC mode for coding a depth block according to an intra prediction mode, e.g., an HEVC base specification intra prediction mode, such as a DC intra prediction mode or one of the directional intra prediction modes. In such examples, the video coder may code a single DC residual value for the depth block.