Abstract: A method includes determining whether a rate distortion cost of a compressed video is above a cost threshold, the compressed video being encoded using a first constant rate factor (CRF). Upon determining the quality of a compressed video is above a cost threshold calculating a second CRF based on the first CRF, and encoding a video associated with the compressed video using the second CRF. Upon determining the quality of a compressed video is below a cost threshold encoding the video using the first CRF and a target bitrate.

Abstract: Systems and methods are described for identifying the video content as spherical video or non-spherical video in response to determining that frame scores and video scores satisfy a threshold level. For example, a plurality of image frames can be extracted from video content, classified in a dual stage process, and scored according to particular classification and scoring mechanisms.

Abstract: A method and system include identifying a plurality of media clips pertaining to an event, for each pair of the plurality of media clips, calculating pairwise relative time offsets for pairs of media clips from the plurality of media clips, calculating, by a processing device, an inconsistency measure, in which the inconsistency measure of a pair of media clips is calculated using at least three relative time offsets and one of the at least three relative time offsets is a relative time offset of the pair of media clips, and synchronizing the plurality of media clips based on resulting calculated inconsistency measures.

Abstract: A method includes identifying a frame of a spherical video as a key frame, storing a compensation component based on position data of a camera in association with the key frame, and compensating for a movement of the camera in a subsequent frame of the spherical video based on the key frame and the compensation component associated with the key frame.

Abstract: Systems and methods are described for identifying the video content as spherical video or non-spherical video in response to determining that frame scores and video scores satisfy a threshold level. For example, a plurality of image frames can be extracted from video content, classified in a dual stage process, and scored according to particular classification and scoring mechanisms.

Abstract: Systems and methods are described for identifying the video content as spherical video or non-spherical video in response to determining that frame scores and video scores satisfy a threshold level. For example, a plurality of image frames can be extracted from video content, classified in a dual stage process, and scored according to particular classification and scoring mechanisms.

Abstract: A method includes identifying a frame of a spherical video as a key frame, storing a compensation component based on position data of a camera in association with the key frame, and compensating for a movement of the camera in a subsequent frame of the spherical video based on the key frame and the compensation component associated with the key frame.

Abstract: Systems and methods are described for identifying the video content as spherical video or non-spherical video in response to determining that frame scores and video scores satisfy a threshold level. For example, a plurality of image frames can be extracted from video content, classified in a dual stage process, and scored according to particular classification and scoring mechanisms.

Abstract: Systems and methods for noise reduction are disclosed herein. The system includes a video codec system that can encode and/or decode video information. A noise representation component can identify flat regions and a quantizer can utilize the identified flat regions to suppress noise during compression. By suppressing noise during compression, the size of the video file to be compressed can be reduced, compression can use less resources and take less time, and the speed at which the compressed information is transferred can benefit. Noise can be reintroduced during the reconstruction of the video. Accordingly, both noise reduction and noise synthesis can be accomplished.

Abstract: Systems and methods for noise reduction are disclosed herein. The system includes a video codec system that can encode and/or decode video information. A noise representation component can identify flat regions and a quantizer can utilize the identified flat regions to suppress noise during compression. By suppressing noise during compression, the size of the video file to be compressed can be reduced, compression can use less resources and take less time, and the speed at which the compressed information is transferred can benefit. Noise can be reintroduced during the reconstruction of the video. Accordingly, both noise reduction and noise synthesis can be accomplished.

Abstract: A method and apparatus for estimating motion and occlusion is disclosed. In one aspect, a method of estimating motion and occlusion between three or more frames in a video stream includes identifying a plurality of motion vector candidates for each of a forward direction and a backward direction, generating a plurality of candidate pairs, determining an energy for at least some of the plurality of candidate pairs using a processor by jointly evaluating the forward motion vector and the backward motion vector of at least some of the plurality of candidate pairs based on interframe difference, spatial motion correlation, temporal motion correlation, and spatial occlusion correlation, and estimating motion and occlusion between the three or more frames by selecting a candidate vector from the plurality of candidate vectors based on the determined energies.

Abstract: A method and apparatus for estimating motion and occlusion is disclosed. In one aspect, a method of estimating motion and occlusion between three or more frames in a video stream includes identifying a plurality of motion vector candidates for each of a forward direction and a backward direction, generating a plurality of candidate pairs, determining an energy for at least some of the plurality of candidate pairs using a processor by jointly evaluating the forward motion vector and the backward motion vector of at least some of the plurality of candidate pairs based on interframe difference, spatial motion correlation, temporal motion correlation, and spatial occlusion correlation, and estimating motion and occlusion between the three or more frames by selecting a candidate vector from the plurality of candidate vectors based on the determined energies.