Abstract: A method includes receiving, at a conference endpoint, video captured using a wide angle lens. The method further includes selecting a view region in a frame of the video. The method further includes selectively applying, based on a size of the view region, deformation correction or distortion correction to the view region to generate a corrected video frame. The method further includes transmitting the corrected video frame to a remote endpoint.

Abstract: A method (1000) for operating cameras (202) in a cascaded network (100), comprising: capturing a first view (1200) with a first lens (326) having a first focal point (328) and a first centroid (352), the first view (1200) depicting a subject (1106); capturing a second view (1202) with a second lens (326) having a second focal point (328) and a second centroid (352); detecting a first location of the subject (1106), relative the first lens (326), wherein detecting the first location of the subject (1106), relative the first lens (326), is based on audio captured by a plurality of microphones (204); estimating a second location of the subject (1106), relative the second lens (326), based on the first location of the subject (1106) relative the first lens (326); selecting a portion (1206) of the second view (1202) as depicting the subject (1106) based on the estimate of the second location of the subject (1106) relative the second lens (326).

Abstract: A method of tracking a presenter during a videoconference, comprising: detecting, in a data stream, data indicating a presence of one or more persons at a videoconferencing endpoint, the data stream comprising a plurality of frames; detecting tracker initiation data (e.g., that a person is actively talking, or that a person has raised their hand, or both) in the data stream; determining a subject of interest responsive to the tracker initiation data, and tracking the subject of interest as they move while making a presentation.

Abstract: A method may include identifying primly camera speaker coordinates of a location of a speaker relative to a primary camera, converting the primary camera speaker coordinates to secondary camera speaker coordinates, the secondary camera speaker coordinates being of the location and relative to a secondary camera, and adjusting, using the secondary camera speaker coordinates of the secondary camera, a view setting of the secondary camera to track the location of the speaker.

Abstract: A real-time method (600) for enhancing facial images (102). Degraded images (102) of a person—such as might be transmitted during a videoconference—are rectified based on a single high definition reference image (604) of a person who is talking. Facial landmarks (501) are used to map (210) image data from the reference image (604) to an intervening image (622) having a landmark configuration like that in a degraded image (102). The degraded images (102) and their corresponding intervening images (622) are blended using an artificial neural network (800, 900) to produce high-quality images (108) of the person who is speaking during a videoconference.

Abstract: Systems and methods are provided for identifying and displaying whiteboard text and/or an active speaker in a video-based presentation, e.g., a video conference. Video images of an environment including a whiteboard may be captured by a video camera system. The video images may be analyzed to detect at least one text-containing area in the environment. Each text-containing area may be analyzed to determine whether it is an area of a whiteboard. When a text-containing area is identified as a whiteboard area, an area of view including the text-containing whiteboard area may be selected for display, e.g., a subset of the full frame captured by the video system. A video feed from the video camera system may be controlled to display the selected area of view at a client device, to provide a useful view of the whiteboard text and/or a speaking person located near the whiteboard text.

Abstract: A method performs zooming based on gesture detection. A visual stream is presented using a first zoom configuration for a zoom state. An attention gesture is detected from a set of first images from the visual stream. The zoom state is adjusted from the first zoom configuration to a second zoom configuration to zoom in on a person in response to detecting the attention gesture. The visual stream is presented using the second zoom configuration after adjusting the zoom state to the second zoom configuration. Whether the person is speaking is determined, from a set of second images from the visual stream. The zoom state is adjusted to the first zoom configuration to zoom out from the person in response to determining that the person is not speaking. The visual stream is presented using the first zoom configuration after adjusting the zoom state to the first zoom configuration.

Abstract: A videoconferencing device at an endpoint determines whether a person is a real person standing in front of a display device or if the person is instead an image rendered by a display device. In the first instance the real person will be included in a video feed for transmission to a remote endpoint. In the second instance, images of the display device on which the person is rendered will not be included in the video feed.

Abstract: A method of tracking a presenter during a videoconference, comprising: detecting, in a data stream, data indicating a presence of one or more persons at a videoconferencing endpoint, the data stream comprising a plurality of frames; detecting tracker initiation data (e.g., that a person is actively talking, or that a person has raised their hand, or both) in the data stream; determining a subject of interest responsive to the tracker initiation data, and tracking the subject of interest as they move while making a presentation.

Abstract: A method (1000) for operating cameras (202) in a cascaded network (100), comprising: capturing a first view (1200) with a first lens (326) having a first focal point (328) and a first centroid (352), the first view (1200) depicting a subject (1106); capturing a second view (1202) with a second lens (326) having a second focal point (328) and a second centroid (352); detecting a first location of the subject (1106), relative the first lens (326), wherein detecting the first location of the subject (1106), relative the first lens (326), is based on audio captured by a plurality of microphones (204); estimating a second location of the subject (1106), relative the second lens (326), based on the first location of the subject (1106) relative the first lens (326); selecting a portion (1206) of the second view (1202) as depicting the subject (1106) based on the estimate of the second location of the subject (1106) relative the second lens (326).

Abstract: A teleconferencing system (100) comprises: a first camera (202) including a first lens (326) having a first focal point (328) and a first centroid (352), and configured to capture a first view (900) corresponding to a subject (702); a second lens (326) having a second focal point (328) and a second centroid (352), and configured to capture a second view (902) corresponding to the subject (702); and a processor (206) coupled to the first camera device (202) and the second camera device (202). The processor (206) is configured to: estimate a first orientation (351) of the subject (702) relative the first lens (326) and a second orientation (351) of the subject relative the second lens (326); and determine that the first orientation (351) is more closely aligned with a first line (307) from the first centroid (352) to the first focal point (328) than is the second orientation (351) aligned with a second line (307) from the second centroid (352) to the second focal point (328).

Abstract: One illustrative method includes: (a) obtaining a video frame sequence having alternating fast and slow exposure frames; (b) applying a convolutional neural network twice to each frame in the video frame sequence, first when the frame is paired with a preceding frame, and again when the frame is paired with a subsequent frame, each time converting a pair of fast and slow exposure frames into an enhanced dynamic range video frame; and (c) outputting an enhanced video frame sequence. In another illustrative method, the convolutional neural network converts pairs of adjacent fast and slow exposure frames into corresponding pairs of enhanced dynamic range video frames. In yet another illustrative method, neighboring video frames for each given video frame are interpolated to form a fast and slow exposure frame pair, which the convolutional neural network converts into a corresponding enhanced dynamic range video frame.

Abstract: A method may include identifying, in a frame of a video feed, a region of interest (ROI) and a background, encoding the background using a first quantization parameter to obtain an encoded low-quality background, encoding the ROI using a second quantization parameter to obtain an encoded high-quality ROI, and encoding location information of the ROI to obtain encoded location information. The method may further include combining the encoded low-quality background, the encoded high-quality ROI, and the encoded location information to obtain a combined package. The method may further include transmitting the combined package to a remote endpoint.

Abstract: A videoconferencing endpoint can adaptively adjust for lens distortion and image deformation depending on the distance of the subject from a camera and the radial distance of the subject from the center of the camera's field of view.

Abstract: A method for tracking movement of a presenter during a videoconference comprises tracking the location of subject of interest; quickly detecting error conditions—such as can occur when a subject of interest moves too quickly or when a subject of interest walks past another person—and quickly reinitiating the tracking sequence to help ensure a positive videoconferencing experience.

Abstract: A method for tracking movement of a presenter during a videoconference comprises tracking the location of subject of interest; quickly detecting error conditions—such as can occur when a subject of interest moves too quickly or when a subject of interest walks past another person—and quickly reinitiating the tracking sequence to help ensure a positive videoconferencing experience.

Abstract: A method includes receiving, at a conference endpoint, video captured using a wide angle lens. The method further includes selecting a view region in a frame of the video. The method further includes selectively applying, based on a size of the view region, deformation correction or distortion correction to the view region to generate a corrected video frame. The method further includes transmitting the corrected video frame to a remote endpoint.

Abstract: A videoconferencing device at an endpoint determines whether a person is a real person standing in front of a display device or if the person is instead an image rendered by a display device. In the first instance the real person will be included in a video feed for transmission to a remote endpoint. In the second instance, images of the display device on which the person is rendered will not be included in the video feed.

Abstract: A videoconferencing device at an endpoint determines whether a person is a real person standing in front of a display device or if the person is instead an image rendered by a display device. In the first instance the real person will be included in a video feed for transmission to a remote endpoint. In the second instance, images of the display device on which the person is rendered will not be included in the video feed.