Abstract:
Described herein are techniques related to noise reduction for image sequences or videos. This Abstract is submitted with the understanding that it will not be used to interpret or limit the scope and meaning of the claims. A noise reduction tool includes a motion estimator configured to estimated motion in the video, a noise spectrum estimator configured to estimate noise in the video, a shot detector configured to trigger the noise estimation process, a noise spectrum validator configured to validate the estimated noise spectrum, and a noise reducer to reduce noise in the video using the estimated noise spectrum.
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 system for video stabilization is provided. The system includes a media component, a transformation component, an offset component and a zoom component. The media component receives a video sequence including at least a first video frame and a second video frame. The transformation component calculates at least a first motion parameter associated with translational motion for the first video frame and at least a second motion parameter associated with the translational motion for the second video frame. The offset component subtracts an offset value generated as a function of a maximum motion parameter and a minimum motion parameter from the first motion parameter and the second motion parameter to generate a set of modified motion parameters. The zoom component determines a zoom value for the video sequence based at least in part on the set of modified motion parameters.
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:
A system for video stabilization is provided. The system includes a media component, a transformation component, an offset component and a zoom component. The media component receives a video sequence including at least a first video frame and a second video frame. The transformation component calculates at least a first motion parameter associated with translational motion for the first video frame and at least a second motion parameter associated with the translational motion for the second video frame. The offset component subtracts an offset value generated as a function of a maximum motion parameter and a minimum motion parameter from the first motion parameter and the second motion parameter to generate a set of modified motion parameters. The zoom component determines a zoom value for the video sequence based at least in part on the set of modified motion parameters.
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 for pull frame interpolation includes receiving an encoded bitstream including information representing a plurality of frames of video data, decoding the plurality of frames, including identifying a plurality of motion vectors indicating motion from a first frame of the plurality of video frames to a second frame of the plurality of video frames, identifying an interpolation point between the first frame and the second frame, identifying a plurality of candidate interpolation motion vectors indicating motion from the first frame to the interpolation point and from the second frame to the interpolation point based on the plurality of motion vectors, selecting an interpolation motion vector from the plurality of candidate interpolation motion vectors based on a metric, and generating an interpolated frame at the interpolation point based on the selected interpolation motion vector, which may include correcting an artifact in the interpolated frame by blending the interpolated 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.