Abstract: A multi-camera video conference call system is provided with a plurality of cameras connected together over a communication network to generate a corresponding plurality of input frame images taken from different perspectives of a video conference room, where the multi-camera video conference call system detects one or more human heads for any meeting participants captured in the input frame images, generates a head bounding box which surrounds each detected human head, extracts a body bounding box which surrounds the detected human head and at least an upper body portion of a meeting participant belonging to the detected human head, generates a participant identification feature embedding from each body bounding box, and performs person re-identification processing on all generated participant identification feature embeddings to determine a count of the meeting participants in the video conference room.

Abstract: A method implements customizable gesture commands. The method includes constructing a set of gesture containers and training a machine learning model, for a gesture container of the set of gesture containers, to detect a performance of a video gesture. The method further includes detecting the performance of the video gesture, from a gesture container of the set of gesture containers, in a video stream using the machine learning model. The method further includes executing, in response to detecting the video gesture, a command assigned to the video gesture by the gesture container.

Abstract: A method including detecting, in a digital image, a set of sub-images matching a selected object type. The method also includes generating a first confidence score that a first sub-image in set of sub-images matches a selected object type. The method also includes generating a second confidence score that a second sub-image in set of sub-images matches the selected object type. The method also includes generating a similarity measure by comparing the first sub-image to the second sub-image. The method also includes removing, responsive to the similarity measure exceeding a similarity threshold value and the first confidence score exceeding the second confidence score, the second sub-image from the set of sub-images. The method also includes processing, after removing, the digital image using the set of sub-images.

Abstract: The number of persons in a still image acquired during a videoconference may change over time due to movement or persons entering or exiting a conference room. Minimizing the number of person identifiers that are tracked is beneficial for framing purposes. Typically, a stream of frames is sent to a far side, such as another endpoint device, for viewing. If the number of persons identified keeps changing, the composition of the stream of frames will be constantly changing as well. By using person identification and the use of timers, movement by the same person or a temporary change in a number or set of persons may be detected without making changes to the number of identifiers and persons being framed. It is only when a change has persisted past a period of time that changes are made to the frames, thereby improving the overall viewing experience.

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: Providing a facilities supervisor notice after a conference room or other common area has been used and is in a messy condition. An image of the conference room obtained after use is evaluated to determine if the conference room is neat. A neatness score is obtained for the conference room. If the score indicates a neatness value above a settable level, the conference room is considered clean and ready for use. If the neatness score indicates a neatness value less than the settable level, the conference room is not ready for use, and a notice is provided to the facilities supervisor to allow a cleaning person to be dispatched. The need to perform the cleanliness or neatness review is triggered by referencing scheduled meetings in a calendaring system, by monitoring the conference room for the presence of individuals having an unscheduled meeting and periodically or randomly.

Abstract: A method implements customizable gesture commands. The method includes constructing a set of gesture containers and training a machine learning model, for a gesture container of the set of gesture containers, to detect a performance of a video gesture. The method further includes detecting the performance of the video gesture, from a gesture container of the set of gesture containers, in a video stream using the machine learning model. The method further includes executing, in response to detecting the video gesture, a command assigned to the video gesture by the gesture container.

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: A method implementing dynamic camera presets. An image is received. A list of bounding boxes and a list of classification values are generated from the image. A set of tags, for the image, are generated from the list of bounding boxes and the list of classification values. A tagged image incorporating the set of tags into the image is presented. In response to a user input, a tag selection identifying a tag of the set of tags is received. View settings are adjusted to focus on a bounding box, from the list of bounding boxes, corresponding to the tag selection. An adjusted image is presented using the view settings.