Abstract:
Implementations generally relate to modifying an appearance of a participant during a video conference. In some implementations, a method includes obtaining at least one frame from a media stream, where the at least one frame includes a first face, and where the first face is an image of a face associated with a user. The method also includes determining a plurality of coordinates within the at least one frame. The method also includes obtaining at least one media content item. The method also includes adding the at least one media content item to the at least one frame based on the plurality of coordinates.
Abstract:
A system for endpoint device-specific stream control for multimedia conferencing may include one or more processors and memory. The one or more processors may perform steps of providing a hosted multimedia conference to participant devices, determining whether each participant device is capable of providing a video stream transmission and providing, to each participant device, video stream controls that provide for controlling video streams of exclusively the other participant devices that are determined to be capable of providing video stream transmissions. The steps may further include receiving a selection of a first video stream control corresponding to a first participant device from second and third participant devices, receiving a video stream from the first participant device, and providing the video stream to the second and third participant devices based at least in part on the received selections of the first video stream control by the second and third participant devices.
Abstract:
Methods and systems are provided allowing for background identification and gesture recognition in video images. A computer-implemented image processing method includes: receiving, using at least one processing circuit, a plurality of image frames of a video; constructing, using at feast one processing circuit, a plurality of statistical models of the plurality of image frames at a plurality of pixel granularity levels; constructing, using at least one processing circuit, a plurality of probabilistic models of an input image frame at a plurality of channel granularity levels based on the plurality of statistical models; merging at least some of the plurality of probabilistic models based on a weighted average to form a single probability image; determining background pixels, based on a probability threshold value, from the single probability image; and determining whether the plurality of image frames, when examined in a particular sequence, conveys a gesture by the object.
Abstract:
A system for providing a trusted peer-based information verification system may include one or more processors and a memory. The one or more processors may provide a multimedia conference to participant devices, and may receive a request to transfer a session of the multimedia conference of a participant device that is characterized by a first multimedia conference capability. The one or more processors may provide a list of target devices associated with the participant device to the participant device, and may receive an indication of a target device from the participant device. The one or more processors may transfer the session of the multimedia conference from the participant device to the target device, wherein the target device is characterized by a second multimedia conference capability that is different than the first multimedia conference capability of the participant device.
Abstract:
Methods and systems are provided allowing for background identification and gesture recognition in video images. A computer-implemented image processing method includes: receiving, using at least one processing circuit, a plurality of image frames of a video; constructing, using at feast one processing circuit, a plurality of statistical models of the plurality of image frames at a plurality of pixel granularity levels; constructing, using at least one processing circuit, a plurality of probabilistic models of an input image frame at a plurality of channel granularity levels based on the plurality of statistical models; merging at least some of the plurality of probabilistic models based on a weighted average to form a single probability image; determining background pixels, based on a probability threshold value, from the single probability image; and determining whether the plurality of image frames, when examined in a particular sequence, conveys a gesture by the object.