Intel Corporation

Mofa (Shanghai) Information Technology Co., Ltd.

Shanghai Movu Technology Co., Ltd.

Zhiqiang Liang

Yu Chen

Bin Wang

Nilesh K Jain

Jinkui Ren

Darshan Iyer

Jinxiang Chai

Congyi Wang

Xingtang Xiong

Tingqian Li

Hongbing Tan

A virtual role-based multimodal interaction method, apparatus and system, a storage medium, and a terminal, where the method includes: acquiring input information, where the input information includes one or more data types; inputting the input information into a perception layer to enable the perception layer to recognize and process the input information according to a data type of the input information to obtain a recognition result; inputting the recognition result into a logic decision-making layer to enable the logic decision-making layer to process the recognition result and generate a drive instruction corresponding to the recognition result; acquiring multimodal virtual content according to the drive instruction, wherein the multimodal virtual content includes at least a virtual role; and outputting the acquired multimodal virtual content.

Virtual role-based multimodal interaction method, apparatus and system, storage medium, and terminal

Systems and methods for recognizing a gesture in a wearable device are disclosed. The system may sense a plurality of sensor measurements during a gesture sensing session, and down-sample the measurements using an adaptive down-sampling interval. The adaptive down-sampling interval may be determined based at least on a fractional part of a ratio of a frame length of the sensor measurements to a specified target length shorter than the frame length. The magnitude of the down-sampled measurements is normalized, and a feature vector may be generated using the normalized measurements. A gesture recognizer module may associate a gesture with the feature vector using gesture classification.

Time domain feature transform for user gestures

Technologies for gesture recognition using downsampling are disclosed. A gesture recognition device may capture gesture data from a gesture measurement device, and downsample the captured data to a predefined number of data points. The gesture recognition device may then perform gesture recognition on the downsampled gesture data to recognize a gesture, and then perform an action based on the recognized gesture. The number of data points to which to downsample may be determined by downsampling to several different numbers of data points and comparing the performance of a gesture recognition algorithm performed on the downsampled gesture data for each different number of data points.

Technologies for adaptive downsampling for gesture recognition

Growing community of inventors

Shanghai, China

Zhiqiang Liang