Abstract: The present disclosure relates to systems, methods, and computer-readable media for selectively identifying image frames from an input video to provide to an image processing model based on camera statistics. For example, systems disclosed herein include receiving an input video and associated camera statistics from a video capturing device. The systems disclosed herein further include identifying select image frames to provide to the image processing model based on the camera statistics and based on an application of the image processing model. The systems disclosed herein further include selectively identifying and providing camera statistics to the image processing model. By selectively providing data to the image processing model based on camera statistics, the systems disclosed herein can leverage capabilities of video capturing devices to significantly reduce the expense of processing resources when utilizing a variety of image processing models.

Abstract: A media processing tool adds custom data to an elementary media bitstream or media container. The custom data indicates nominal range of samples of media content, but the meaning of the custom data is not defined in the codec format or media container format. For example, the custom data indicates the nominal range is full range or limited range. For playback, a media processing tool parses the custom data and determines an indication of media content type. A rendering engine performs color conversion operations whose logic changes based at least in part on the media content type. In this way, a codec format or media container format can in effect be extended to support full nominal range media content as well as limited nominal range media content, and hence preserve full or correct color fidelity, while maintaining backward compatibility and conformance with the codec format or media container format.

Abstract: The present disclosure relates to systems, methods, and computer-readable media for selectively identifying image frames from an input video to provide to an image processing model based on camera statistics. For example, systems disclosed herein include receiving an input video and associated camera statistics from a video capturing device. The systems disclosed herein further include identifying select image frames to provide to the image processing model based on the camera statistics and based on an application of the image processing model. The systems disclosed herein further include selectively identifying and providing camera statistics to the image processing model. By selectively providing data to the image processing model based on camera statistics, the systems disclosed herein can leverage capabilities of video capturing devices to significantly reduce the expense of processing resources when utilizing a variety of image processing models.

Abstract: The techniques disclosed herein enable systems to perform automatic camera rotation for multi-posture devices (e.g., tablet devices, foldable devices, external displays with built-in webcams) irrespective of a current posture of the computing device. This is accomplished by reformatting an image captured by an image sensor using an image signal processer prior to encoding for output. To reformat the image, the computing device determines an angle of rotation for the computing device relative to a default posture. The image is then rotated based on the angle of rotation such that the image appears right side up for the current posture. Subsequently, the image is cropped from its original aspect ratio to a predetermined aspect ratio. Finally, the image is encoded to generate an output stream that can be received by an application. In this way, the system maintains visual consistency even as a user rotates the device.

Abstract: A media processing tool adds custom data to an elementary media bitstream or media container. The custom data indicates nominal range of samples of media content, but the meaning of the custom data is not defined in the codec format or media container format. For example, the custom data indicates the nominal range is full range or limited range. For playback, a media processing tool parses the custom data and determines an indication of media content type. A rendering engine performs color conversion operations whose logic changes based at least in part on the media content type. In this way, a codec format or media container format can in effect be extended to support full nominal range media content as well as limited nominal range media content, and hence preserve full or correct color fidelity, while maintaining backward compatibility and conformance with the codec format or media container format.

Abstract: The present disclosure relates to systems, methods, and computer-readable media for selectively identifying pixel data to provide as an input to an image processing model based on motion data associated with the content of a digital video. For example, systems disclosed herein include receiving a compressed digital video and decompressing the compressed digital video to generate a decompressed digital video. The systems disclosed herein further include extracting or otherwise identifying motion data while decompressing the compressed digital video. The systems disclosed herein also include analyzing the motion data to determine a subset of pixel data from the decompressed digital video to provide as input to an image processing model trained to generate an output based on input pixel data.

Abstract: The present disclosure relates to systems, methods, and computer-readable media for selectively identifying pixel data to provide as an input to an image processing model based on motion data associated with the content of a digital video. For example, systems disclosed herein include receiving a compressed digital video and decompressing the compressed digital video to generate a decompressed digital video. The systems disclosed herein further include extracting or otherwise identifying motion data while decompressing the compressed digital video. The systems disclosed herein also include analyzing the motion data to determine a subset of pixel data from the decompressed digital video to provide as input to an image processing model trained to generate an output based on input pixel data.

Abstract: A method of providing environmental information to an electronic device includes, at the electronic device, receiving ambient light from a surrounding environment of the electronic device with one or more camera sensors in data communication with a processor and capturing a raw pattern with the camera sensor, wherein the raw pattern includes light intensity information and light spectrum information. The method further includes deriving at least one ambient light value from the light intensity information and light spectrum information and providing the ambient light value to the processor of the electronic device.

Abstract: A method of providing environmental information to an electronic device includes, at the electronic device, receiving ambient light from a surrounding environment of the electronic device with one or more camera sensors in data communication with a processor and capturing a raw pattern with the camera sensor, wherein the raw pattern includes light intensity information and light spectrum information. The method further includes deriving at least one ambient light value from the light intensity information and light spectrum information and providing the ambient light value to the processor of the electronic device.

Abstract: A media processing tool adds custom data to an elementary media bitstream or media container. The custom data indicates nominal range of samples of media content, but the meaning of the custom data is not defined in the codec format or media container format. For example, the custom data indicates the nominal range is full range or limited range. For playback, a media processing tool parses the custom data and determines an indication of media content type. A rendering engine performs color conversion operations whose logic changes based at least in part on the media content type. In this way, a codec format or media container format can in effect be extended to support full nominal range media content as well as limited nominal range media content, and hence preserve full or correct color fidelity, while maintaining backward compatibility and conformance with the codec format or media container format.

Abstract: A media processing tool adds custom data to an elementary media bitstream or media container. The custom data indicates nominal range of samples of media content, but the meaning of the custom data is not defined in the codec format or media container format. For example, the custom data indicates the nominal range is full range or limited range. For playback, a media processing tool parses the custom data and determines an indication of media content type. A rendering engine performs color conversion operations whose logic changes based at least in part on the media content type. In this way, a codec format or media container format can in effect be extended to support full nominal range media content as well as limited nominal range media content, and hence preserve full or correct color fidelity, while maintaining backward compatibility and conformance with the codec format or media container format.

Abstract: An image sensor is misaligned with an operating orientation. Misalignment information may be registered with an operating system. Misaligned image data may be transformed as a final processing act before being delivered to an application. A method of transforming image misalignment. Image data having a first orientation is received from an image sensor at a first computing component of a computing device. The image data is transformed using misalignment information to transformed image data having a second orientation. Immediately after transforming the image data, the transformed image data is communicated from a final computing component to an application.

Abstract: Video image stabilization provides better performance on a generic platform for computing devices by evaluating available multimedia digital signal processing components, and selecting the available components to utilize according to a hierarchy structure for video stabilization performance for processing parts of the video stabilization. The video stabilization has improved motion vector estimation that employs refinement motion vector searching according to a pyramid block structure relationship starting from a downsampled resolution version of the video frames. The video stabilization also improves global motion transform estimation by performing a random sample consensus approach for processing the local motion vectors, and selection criteria for motion vector reliability. The video stabilization achieves the removal of hand shakiness smoothly by real-time one-pass or off-line two-pass temporal smoothing with error detection and correction.

Abstract: A media processing tool adds custom data to an elementary media bitstream or media container. The custom data indicates nominal range of samples of media content, but the meaning of the custom data is not defined in the codec format or media container format. For example, the custom data indicates the nominal range is full range or limited range. For playback, a media processing tool parses the custom data and determines an indication of media content type. A rendering engine performs color conversion operations whose logic changes based at least in part on the media content type. In this way, a codec format or media container format can in effect be extended to support full nominal range media content as well as limited nominal range media content, and hence preserve full or correct color fidelity, while maintaining backward compatibility and conformance with the codec format or media container format.

Abstract: The present disclosure relates to systems, methods, and computer-readable media for selectively identifying pixel data to provide as an input to an image processing model based on motion data associated with the content of a digital video. For example, systems disclosed herein include receiving a compressed digital video and decompressing the compressed digital video to generate a decompressed digital video. The systems disclosed herein further include extracting or otherwise identifying motion data while decompressing the compressed digital video. The systems disclosed herein also include analyzing the motion data to determine a subset of pixel data from the decompressed digital video to provide as input to an image processing model trained to generate an output based on input pixel data.

Abstract: The present disclosure relates to systems, methods, and computer-readable media for selectively identifying image frames from an input video to provide to an image processing model based on camera statistics. For example, systems disclosed herein include receiving an input video and associated camera statistics from a video capturing device. The systems disclosed herein further include identifying select image frames to provide to the image processing model based on the camera statistics and based on an application of the image processing model. The systems disclosed herein further include selectively identifying and providing camera statistics to the image processing model. By selectively providing data to the image processing model based on camera statistics, the systems disclosed herein can leverage capabilities of video capturing devices to significantly reduce the expense of processing resources when utilizing a variety of image processing models.

Abstract: Methods and devices for compensating for detected motion when capturing an image may include determining at least one of a global movement of an imaging device and a local movement of one or more objects in a scene captured by the imaging device. The methods and devices may include comparing at least one of the global movement and the local movement to a movement threshold related to a current mode of operation of the imaging device. The methods and devices may include automatically selecting a mode of operation for the imaging device when at least one of the global movement and the local movement exceeds the movement threshold, wherein the selected mode of operation reduces blur in the captured image. The methods and devices may include transmitting information about the mode of operation.

Abstract: Methods and devices for enabling controls of an imaging device may include receiving a data stream with a request for at least one control of an imaging device, wherein the at least one control is related to Universal Serial Bus (USB) video. The methods and devices may include identifying a defined functionality of the at least one control and transmitting the data stream to the imaging device to specify the operation of the imaging device based on the defined functionality of the at least one control. The methods and devices may also include generating metadata information from received video frame packets from an imaging device. The methods and devices may include identifying metadata information in the header of a video packet when the header size exceeds the standard header size. The methods and devices may include generating a metadata buffer with the identified metadata information.

Abstract: A media processing tool adds custom data to an elementary media bitstream or media container. The custom data indicates nominal range of samples of media content, but the meaning of the custom data is not defined in the codec format or media container format. For example, the custom data indicates the nominal range is full range or limited range. For playback, a media processing tool parses the custom data and determines an indication of media content type. A rendering engine performs color conversion operations whose logic changes based at least in part on the media content type. In this way, a codec format or media container format can in effect be extended to support full nominal range media content as well as limited nominal range media content, and hence preserve full or correct color fidelity, while maintaining backward compatibility and conformance with the codec format or media container format.

Abstract: An image sensor is misaligned with an operating orientation. Misalignment information may be registered with an operating system. Misaligned image data may be transformed as a final processing act before being delivered to an application. A method of transforming image misalignment. Image data having a first orientation is received from an image sensor at a first computing component of a computing device. The image data is transformed using misalignment information to transformed image data having a second orientation. Immediately after transforming the image data, the transformed image data is communicated from a final computing component to an application.