Abstract: In one embodiment, a computing system may access a video including a first frame and a second frame. The computing system may determine first sampling locations for the first frame and determine second sampling locations for the second frame by transforming the first sampling locations to the second frame according to an optical flow between the first frame and the second frame. The computing system may detect one or more invalid second sampling locations based on determining pixels in the first frame corresponding to the first sampling locations do not match pixels in the second frame corresponding to the second sampling locations. The computing system may reject the one or more invalid second sampling locations to determine third sampling locations for the second frame. The computing system may generate a sample of the video.

Abstract: In one embodiment, a computing system may access a video including a first frame and a second frame. The computing system may determine first sampling locations for the first frame and determine second sampling locations for the second frame by transforming the first sampling locations to the second frame according to an optical flow between the first frame and the second frame. The computing system may select a subset of the second sampling locations based on a comparison between pixels in the first frame corresponding to the first sampling locations and pixels in the second frame corresponding to the second sampling locations. The computing system may define one or more rejection areas in the second frame based on the subset of the second sampling locations to determine third sampling locations in areas outside of the rejection areas. The computing system may generate a sample of the video.

Abstract: In one embodiment, a computing system may receive a video including a sequence of frames. The computing system may access a three-dimensional mask that specifies pixel-sampling locations, the three-dimensional mask having a first dimension and a second dimension corresponding to a spatial domain and a third dimension corresponding to a temporal domain. Blue noise property may be present in the pixel-sampling locations that are associated with each of a plurality of two-dimensional spatial slices of the three-dimensional mask in the spatial domain and the pixel-sampling locations that are associated with each of a plurality of one-dimensional temporal slices of the three-dimensional mask in the temporal domain. The computing system may generate a sample of the video by sampling the sequence of frames using the three-dimensional mask.

Abstract: In one embodiment, a computing system may access a video including a first frame and a second frame. The computing system may determine first sampling locations for the first frame and determine second sampling locations for the second frame by transforming the first sampling locations to the second frame according to an optical flow between the first frame and the second frame. The computing system may select a subset of the second sampling locations based on a comparison between pixels in the first frame corresponding to the first sampling locations and pixels in the second frame corresponding to the second sampling locations. The computing system may define one or more rejection areas in the second frame based on the subset of the second sampling locations to determine third sampling locations in areas outside of the rejection areas. The computing system may generate a sample of the video.

Abstract: In one embodiment, a computing system may receive a video including a sequence of frames. The computing system may access a three-dimensional mask that specifies pixel-sampling locations, the three-dimensional mask having a first dimension and a second dimension corresponding to a spatial domain and a third dimension corresponding to a temporal domain. Blue noise property may be present in the pixel-sampling locations that are associated with each of a plurality of two-dimensional spatial slices of the three-dimensional mask in the spatial domain and the pixel-sampling locations that are associated with each of a plurality of one-dimensional temporal slices of the three-dimensional mask in the temporal domain. The computing system may generate a sample of the video by sampling the sequence of frames using the three-dimensional mask.