Abstract: A video identifier uniquely identifying a video captured by a camera is generated. The video includes video frames and optionally concurrently captured audio as well as video metadata describing the video. Video data is extracted from at least two of the video's frames. By combining the extracted video data in an order specified by an identifier generation protocol, an extracted data object is generated. The extracted data object is hashed to generate the unique media identifier, which is stored in association with the video. The identifier generation protocol may indicate the portions of the video data to extract, such as video data corresponding to particular video frames and audio data corresponding to particular audio samples. The extracted data object may include a size of particular video frames, a number of audio samples in the video, or the duration of the video, for example.

Abstract: A camera identifies a physical object positioned in a workspace. A display displays first digital information into the workspace. A layering module treats the physical object as a first layer in the workspace and treats the first digital information as a second layer in the workspace. A controller controls the visual adjacency of the first and second layers via display of the first digital information.

Abstract: A video identifier uniquely identifying a video captured by a camera is generated. The video includes video frames and optionally concurrently captured audio as well as video metadata describing the video. Video data is extracted from at least two of the video's frames. By combining the extracted video data in an order specified by an identifier generation protocol, an extracted data object is generated. The extracted data object is hashed to generate the unique media identifier, which is stored in association with the video. The identifier generation protocol may indicate the portions of the video data to extract, such as video data corresponding to particular video frames and audio data corresponding to particular audio samples. The extracted data object may include a size of particular video frames, a number of audio samples in the video, or the duration of the video, for example.

Abstract: A video identifier uniquely identifying a video captured by a camera is generated. The video includes video frames and optionally concurrently captured audio as well as video metadata describing the video. Video data is extracted from at least two of the video's frames. By combining the extracted video data in an order specified by an identifier generation protocol, an extracted data object is generated. The extracted data object is hashed to generate the unique media identifier, which is stored in association with the video. The identifier generation protocol may indicate the portions of the video data to extract, such as video data corresponding to particular video frames and audio data corresponding to particular audio samples. The extracted data object may include a size of particular video frames, a number of audio samples in the video, or the duration of the video, for example.

Abstract: A video identifier uniquely identifying a video captured by a camera is generated. The video includes video frames and optionally concurrently captured audio as well as video metadata describing the video. Video data is extracted from at least two of the video's frames. By combining the extracted video data in an order specified by an identifier generation protocol, an extracted data object is generated. The extracted data object is hashed to generate the unique media identifier, which is stored in association with the video. The identifier generation protocol may indicate the portions of the video data to extract, such as video data corresponding to particular video frames and audio data corresponding to particular audio samples. The extracted data object may include a size of particular video frames, a number of audio samples in the video, or the duration of the video, for example.

Abstract: A video identifier uniquely identifying a video captured by a camera is generated. The video includes video frames and optionally concurrently captured audio as well as video metadata describing the video. Video data is extracted from at least two of the video's frames. By combining the extracted video data in an order specified by an identifier generation protocol, an extracted data object is generated. The extracted data object is hashed to generate the unique media identifier, which is stored in association with the video. The identifier generation protocol may indicate the portions of the video data to extract, such as video data corresponding to particular video frames and audio data corresponding to particular audio samples. The extracted data object may include a size of particular video frames, a number of audio samples in the video, or the duration of the video, for example.

Abstract: A video identifier uniquely identifying a video captured by a camera is generated. The video includes video frames and optionally concurrently captured audio as well as video metadata describing the video. Video data is extracted from at least two of the video's frames. By combining the extracted video data in an order specified by an identifier generation protocol, an extracted data object is generated. The extracted data object is hashed to generate the unique media identifier, which is stored in association with the video. The identifier generation protocol may indicate the portions of the video data to extract, such as video data corresponding to particular video frames and audio data corresponding to particular audio samples. The extracted data object may include a size of particular video frames, a number of audio samples in the video, or the duration of the video, for example.

Abstract: A cloud video system selectively uploads a high-resolution video and instructs one or more client devices to perform distributed processing on the high-resolution video. A client device registers high-resolution videos accessed by the client device from a camera communicatively coupled to the client device. A portion of interest within a low-resolution video transcoded from the high-resolution video is selected. A task list is generated specifying the selected portion of the high-resolution video and at least one task to perform on the portion of the high-resolution video. Commands are transmitted to prompt the client device to perform the at least one task on the specified portion of the high-resolution video according to the task list. The specified portion of the high-resolution video is modified according to the task list and uploaded to the cloud. Example tasks include transcoding, applying edits, extracting metadata, and generating highlight tags.

Abstract: A cloud video system selectively uploads a high-resolution video and instructs one or more client devices to perform distributed processing on the high-resolution video. A client device registers high-resolution videos accessed by the client device from a camera communicatively coupled to the client device. A portion of interest within a low-resolution video transcoded from the high-resolution video is selected. A task list is generated specifying the selected portion of the high-resolution video and at least one task to perform on the portion of the high-resolution video. Commands are transmitted to prompt the client device to perform the at least one task on the specified portion of the high-resolution video according to the task list. The specified portion of the high-resolution video is modified according to the task list and uploaded to the cloud. Example tasks include transcoding, applying edits, extracting metadata, and generating highlight tags.

Abstract: An example system in accordance with aspects of the present disclosure includes a controller and a camera communicatively coupled to the controller to capture an image of a work surface. A projector is also provided and is coupled to the controller to project an illumination pattern onto the work surface during image capture by the camera.

Abstract: An imaging system includes a sensor array of sensor elements to convert incident light to detections. Plural detection accumulators are provided to store detections. Switches alternatively route detections from a sensor element selectively to n?3 members of a set of said detection accumulators. An imaging process includes converting incident light to detections, and routing detections so as to partition them among n?3 accumulators.

Abstract: In one example, a projection capture system includes: a visible light projector to project a pattern on to a surface of a GUI control object placed on or above a work surface; a visible light camera to capture an image of the pattern projected on to the surface of the control object; and a controller operatively connected to the projector and the camera. Programming on the controller determines (1) a lateral position of the pattern relative to a reference position associated with the work surface based on the pattern image captured by the camera and (2) a height of the pattern above the work surface based on the lateral position of the pattern.

Abstract: A camera identifies a physical object positioned in a workspace. A display displays first digital information into the workspace. A layering module treats the physical object as a first layer in the workspace and treats the first digital information as a second layer in the workspace. A controller controls the visual adjacency of the first and second layers via display of the first digital information.

Abstract: An imaging system includes a sensor array of sensor elements to convert incident light to detections. Plural detection accumulators are provided to store detections. Switches alternatively route detections from a sensor element selectively to n?3 members of a set of said detection accumulators. An imaging process includes converting incident light to detections, and routing detections so as to partition them among n?3 accumulators.

Abstract: In one example, a projection capture system includes: a visible light projector to project a pattern on to a surface of a GUI control object placed on or above a work surface; a visible light camera to capture an image of the pattern projected on to the surface of the control object; and a controller operatively connected to the projector and the camera. Programming on the controller determines (1) a lateral position of the pattern relative to a reference position associated with the work surface based on the pattern image captured by the camera and (2) a height the pattern above the work surface based on the lateral position of the pattern.

Abstract: In one implementation, a method scans a media to provide a first image and a second image. The method further subtracts the first image from the second image.

Abstract: A method of document rehabilitation typically includes providing an original document having a set of desirable markings that are substantially achromatic, and a set of undesirable markings, and generating an image file that includes color data corresponding to the original document. A transform filter may be applied to the image file so that the color data for each undesirable marking is mapped to a non-reproduced color, and the color data for each desirable marking is unchanged.

Abstract: A printing component receives media, applies print imaging thereto, and delivers the media to a first location. The apparatus selectively applies at least one calibration mark as the print imaging. An imaging component receives the imaged media at a second location and produces scan data representative thereof. The apparatus selectively analyzes the at least one calibration mark and produces calibration data.

Abstract: A printing component receives media, applies print imaging thereto, and delivers the media to a first location. The apparatus selectively applies at least one calibration mark as the print imaging. An imaging component receives the imaged media at a second location and produces scan data representative thereof. The apparatus selectively analyzes the at least one calibration mark and produces calibration data.

Abstract: A method of document rehabilitation typically includes providing an original document having a set of desirable markings that are substantially achromatic, and a set of undesirable markings, and generating an image file that includes color data corresponding to the original document. A transform filter may be applied to the image file so that the color data for each undesirable marking is mapped to a non-reproduced color, and the color data for each desirable marking is unchanged.