Microsoft Technology Licensing, LLC

Aviv Hurvitz

Eyal Krupka

Ido Leichter

Yoni Smolin

Moshe David

Ilya Gurvich

Xuedong D Huang

Wei Xiong

Adi Diamant

Amit Kumar Agarwal

Lijuan Qin

Xiong Xiao

Shixiong Zhang

Karen Master Ben-Dor

Raz Halaly

Lingfeng Wu

Kfir Karmon

Yuval Tzairi

Aharon Bar-Hillel

Qingfen Lin

Alon Vinnikov

Arash Ghanaie-sichanie

Noam Bloom

In a system including a processor and memory, the memory includes instructions that, when executed by the processor, cause the processor to control the system to perform receiving a video stream capturing objects; identifying, based on the received video stream, object areas corresponding to the objects, respectively; tracking the object areas in the received video stream; generating, based on the tracking of the object areas, visual data sets at a plurality of times, wherein each visual data set is generated at a different time and includes visual data representing each object area; determining a priority of each visual data in each visual data set; selecting, based on the determined priority of each visual data, a group of the visual data to be transmitted to a remote system; and transmitting, to the remote system, the selected group of the visual data.

Object data generation for remote image processing

A method for facilitating a remote conference includes receiving a digital video and a computer-readable audio signal. A face recognition machine is operated to recognize a face of a first conference participant in the digital video, and a speech recognition machine is operated to translate the computer-readable audio signal into a first text. An attribution machine attributes the text to the first conference participant. A second computer-readable audio signal is processed similarly, to obtain a second text attributed to a second conference participant. A transcription machine automatically creates a transcript including the first text attributed to the first conference participant and the second text attributed to the second conference participant.

Computerized intelligent assistant for conferences

A gesture recognition method comprises receiving at a processor from a sensor a sequence of captured signal frames for extracting hand pose information for a hand and using at least one trained predictor executed on the processor to extract hand pose information from the received signal frames. For at least one defined gesture, defined as a time sequence comprising hand poses, with each of the hand poses defined as a conjunction or disjunction of qualitative propositions relating to interest points on the hand, truth values are computed for the qualitative propositions using the hand pose information extracted from the received signal frames, and execution of the gesture is tracked, by using the truth values to determine which of the hand poses in the time sequence have already been executed and which of the hand poses in the time sequence is expected next.

Gesture recognition

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Aviv Hurvitz