Gesture observation likelihood modeling method for three-dimensional tracking

Abstract

The invention provides a gesture observation likelihood modeling method for three-dimensional tracking. Firstly, a gesture state model and ormation of the scene where the gesture is located are defined as a similarity measurement likelihood model; the gesture state model adopts a classic three-dimensional gesture modeling method; the information of the scene where the gesture is located mainly relates to depth information similarity measurement extraction of a three-dimensional scene; and then, a gesture observation likelihood modeling method is created according to the foreground informationof the classic three-dimensional gesture modeling method and the high-dimensional well depth information matched with the Chamfer distance, and a three-dimensional tracked gesture observation likelihood model is obtained according to the gesture contour and the classic three-dimensional gesture modeling result.

Description

technical field [0001] The invention belongs to the field of gesture estimation, in particular to a three-dimensional tracking gesture observation likelihood modeling method. Background technique [0002] With the development and popularization of artificial intelligence technology, the modeling and recognition of gesture gestures are more and more applied in human emotion recognition and intelligent traffic control. To get better understanding and recognition results, it is necessary to establish An efficient gesture model, especially the state tracking of gestures is the most widely used in gesture understanding and recognition, but the currently used gesture modeling method still follows the principle of gradient descent in the later specific recognition, so it cannot be avoided Falling into the embarrassment of local minima, in order to solve this problem, the present invention proposes a gesture modeling based on a three-dimensional tracking gesture observation likeliho...

AI Technical Summary

Problems solved by technology

[0002] With the development and popularization of artificial intelligence technology, the modeling and recognition of gesture gestures are more and more applied in human emotion recognition and intelligent traffic control. To get better understanding and recognition results, it is necessary to establish An efficient gesture model, especially the state tracking of gestures is the most widely used in gesture understanding and recognition, but the currently used gesture modeling method still follows the principle of gradient descent in the later specific recognition, so it cannot be avoided Falling into the embarrassment of local minima, in order to solve this problem, the present invention proposes a gesture modeling based on a three-dimensional tracking gesture observation likelihood modeling method, so the gesture observation relief model oriented to three-dimensional tracking of the present invention is also in this background came into being

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