Abstract: A camera image processor receives frames from an image sensor of the camera. While continuing to receive frames from the image sensor, the camera image processor detecting an action within one or more frames of the received frames, for example using a convolution neural network trained to recognize one or more actions. While continuing to receive frames from the image sensor, the camera image processor captures the one or more frames with the detected action, for example as a still image, or as a slow-motion portion of a video that includes the received frames.

Abstract: A camera image processor receives frames from an image sensor of the camera. While continuing to receive frames from the image sensor, the camera image processor detecting an action within one or more frames of the received frames, for example using a convolution neural network trained to recognize one or more actions. While continuing to receive frames from the image sensor, the camera image processor captures the one or more frames with the detected action, for example as a still image, or as a slow-motion portion of a video that includes the received frames.

Abstract: Methods, systems, and devices for low-cost video segmentation are described. A media file may include multiple frames. Information for pixels in a first frame and pixels in a subsequent frame may be discarded based on segmentation maps computed for the first and subsequent frame. After discarding the pixel information, motion information may be determined for the remaining pixels in the first and subsequent frame. The segmentation maps generated for the first and subsequent frames and the determined motion information may be used to compute one or more additional segmentation maps for one or more additional frames that are temporally located between the first and subsequent frame. After computing segmentation maps for all or a portion of the frames in the media file, a modified version of the frames may be output based on the computed segmentation maps.

Abstract: Methods, devices, and systems for simulating motion blur are disclosed. In some aspects, a device includes a memory and one or more processors coupled to the memory. The one or more processors may be configured to receive a plurality of frames, identify an object of interest within the plurality of frames, track the object of interest within the plurality of frames, align the object of interest within the plurality of frames, and generate a final frame based on blending the aligned plurality of frames.

Abstract: Methods, devices, and systems for simulating motion blur are disclosed. In some aspects, a device includes a memory and one or more processors coupled to the memory. The one or more processors may be configured to receive a plurality of frames, identify an object of interest within the plurality of frames, track the object of interest within the plurality of frames, align the object of interest within the plurality of frames, and generate a final frame based on blending the aligned plurality of frames.

Abstract: A system comprising one or more storage devices configured to store data representing a video sequence, and one or more processors. The storage device(s) store instructions that, when executed, cause the at least one processor to: determine a region of interest for an object in a video frame of a video sequence, determine motion information between the video frame and a later video frame of the video sequence, determine, based on the region of interest and the motion information, an adjusted region of interest in the later video frame, and apply a mean shift algorithm to identify, based on the adjusted region of interest, the object in the later video frame.

Abstract: A method for generating a cinemagraph is described. The method includes determining optical flow information for a frame sequence. The method also includes performing image stabilization using the optical flow information to produce a stabilized frame sequence. The method further includes performing object tracking across the frame sequence using motion vector information to determine an object region of interest (ROI) of an object in each frame in the frame sequence. The method additionally includes generating a masking area for each frame in the stabilized frame sequence based on the object ROI for the frame. The method also includes merging the masking areas and the stabilized frame sequence to generate the cinemagraph.