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.