Devices and methods for single or multi-user gesture detection using computer vision
AssigneeHuawei Technologies Co., Ltd.
InventorsYannick VERDIE, Zi Hao YANG, Deepak SRIDHAR, Juwei LU
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Abstract
Methods and devices are described for computer vision-based gesture detection. From a frame of image data, extracted locations of keypoints of a detected hand are obtained. The extracted locations are normalized to obtain normalized features. The normalized features are processed using a trained decision tree ensemble to generate a probability of a valid gesture for the detected hand. The generated probability is compared with a defined decision threshold to generate a binary classification to classify the detected hand as a valid gesture or invalid gesture.
Claims20
A device comprising:
- at least one processing unit coupled to a memory storing computer-executable instructions thereon, wherein the instructions, when executed by the at least one processing unit, cause the device to:
- obtain extracted locations of keypoints of a detected hand in a frame of image data;
- normalize the extracted locations to obtain normalized features;
- process the normalized features using a trained decision tree ensemble to generate a probability of a valid gesture for the detected hand;
- and
- compare the generated probability with a defined decision threshold to generate a binary classification to classify the detected hand as a valid gesture or invalid gesture.
A method comprising:
- obtaining extracted locations of keypoints of a detected hand in a frame of image data;
- normalizing the extracted locations to obtain normalized features;
- processing the normalized features using a trained decision tree ensemble to generate a probability of a valid gesture for the detected hand;
- and
- comparing the generated probability with a defined decision threshold to generate a binary classification to classify the detected hand as a valid gesture or invalid gesture.
A non-transitory computer readable medium having instructions encoded thereon, wherein the instructions, when executed by at least one processing unit of a computing device, cause the computing device to:
- obtain extracted locations of keypoints of a detected hand in a frame of image data;
- normalize the extracted locations to obtain normalized features;
- process the normalized features using a trained decision tree ensemble to generate a probability of a valid gesture for the detected hand;
- and
- compare the generated probability with a defined decision threshold to generate a binary classification to classify the detected hand as a valid gesture or invalid gesture.
Dependencies are inferred from the claim text.