Abstract: Described are multiple cameras in a conference room, each pointed in a different direction. A primary camera includes a microphone array to perform sound source localization (SSL). The SSL is used in combination with a video image to identify the speaker from among multiple individuals that appear in the video image. Pose information of the speaker is developed. Pose information of each individual identified in each other camera is developed. The speaker pose information is compared to the pose information of the individuals from the other cameras. The best match for each other camera is selected as the speaker in that camera. The speaker views of each camera are compared to determine the speaker view with the most frontal view of the speaker. That camera is selected to provide the video for provision to the far end.

Abstract: A method including generating, by applying a three-dimensional pose estimation model to an original image generated by a camera, estimated three-dimensional poses for people in the original image. The estimated three-dimensional poses include distances from the camera. The method further includes determining, using the distances, a far people subset of the people. Each person of the far people subset corresponds to a distance from the camera exceeding a threshold distance. The method further includes, deriving, for the far people subset, regions of interest, upscaling a region of interest for a person of the far people subset to generate an upscaled region of interest, and generating, from the original image and the upscaled region of interest, an enhanced image.

Abstract: Distributed machine learning inference includes acquiring, by an input device, an input frame, executing, by an embedded processor of the input device, a model feature extractor on the input frame to obtain extracted features of the input frame, and transmitting the extracted features from the input device to a processing device. The processing device executes a model feature aggregator to process the plurality of extracted features and obtain a model result.

Abstract: A system for preventing private image data captured at an endpoint from being shared during a videoconference is provided. A user can select three-dimensional regions which will not be seen during a videoconference while areas in front of the designated regions remain viewable.

Abstract: A system for preventing private image data captured at an endpoint from being shared during a videoconference is provided. A user can select three-dimensional regions which will not be seen during a videoconference while areas in front of the designated regions remain viewable.

Abstract: Multiple cameras in a conference room, each pointed in a different direction and including a microphone array to perform sound source localization (SSL). The SSL is used in combination with the video image to identify the speaker from among multiple individuals that appear in the video image. Neural network or machine learning processing is performed on the identified speaker to determine the quality of the front or facial view of the speaker. The best view of the speaker's face from the various cameras is selected to be provided to the far end. If no view is satisfactory, a default view is selected and that is provided to the far end. The use of the SSL allows selection of the proper individual from a group of individuals in the conference room, so that only the speaker's head is analyzed for the best facial view and then framed for transmission.

Abstract: Described are multiple cameras in a conference room, each pointed in a different direction. A primary camera includes a microphone array to perform sound source localization (SSL). The SSL is used in combination with a video image to identify the speaker from among multiple individuals that appear in the video image. Pose information of the speaker is developed. Pose information of each individual identified in each other camera is developed. The speaker pose information is compared to the pose information of the individuals from the other cameras. The best match for each other camera is selected as the speaker in that camera. The speaker views of each camera are compared to determine the speaker view with the most frontal view of the speaker. That camera is selected to provide the video for provision to the far end.

Abstract: Multiple cameras in a conference room, each pointed in a different direction and including a microphone array to perform sound source localization (SSL). The SSL is used in combination with the video image to identify the speaker from among multiple individuals that appear in the video image. Neural network or machine learning processing is performed on the identified speaker to determine the quality of the front or facial view of the speaker. The best view of the speaker's face from the various cameras is selected to be provided to the far end. If no view is satisfactory, a default view is selected and that is provided to the far end. The use of the SSL allows selection of the proper individual from a group of individuals in the conference room, so that only the speaker's head is analyzed for the best facial view and then framed for transmission.

Abstract: A teleconferencing system, comprising: a camera, wherein the camera is configured to capture an image data stream comprising one or more image data frames in accordance with one or more image-capture parameters; and a processor coupled to the camera, wherein the processor is configured to: receive the image data stream from the camera; determine a region of interest within an image data frame of the image data stream; identify a sub-portion of the image data frame corresponding to the region of interest; evaluate a quality of image data corresponding to the sub-portion; determine that the quality of the image data corresponding to the sub-portion is below one or more predetermined quality thresholds; update one or more of the image-capture parameters of the camera, responsive to determining that the quality of the image data corresponding to the sub-portion is below the one or more predetermined quality thresholds.

Abstract: A teleconferencing system, comprising: a camera, wherein the camera is configured to capture an image data stream comprising one or more image data frames in accordance with one or more image-capture parameters; and a processor coupled to the camera, wherein the processor is configured to: receive the image data stream from the camera; determine a region of interest within an image data frame of the image data stream; identify a sub-portion of the image data frame corresponding to the region of interest; evaluate a quality of image data corresponding to the sub-portion; determine that the quality of the image data corresponding to the sub-portion is below one or more predetermined quality thresholds; update one or more of the image-capture parameters of the camera, responsive to determining that the quality of the image data corresponding to the sub-portion is below the one or more predetermined quality thresholds.