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Hand gesture recognition method based on multi-feature fusion and fingertip detecting

A multi-feature fusion, fingertip detection technology, applied in the field of gesture recognition, can solve the problem of low gesture recognition rate

Active Publication Date: 2015-01-21
ZHEJIANG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method can effectively solve the problem of low gesture recognition rate in complex scenes and meet the real-time requirements

Method used

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  • Hand gesture recognition method based on multi-feature fusion and fingertip detecting
  • Hand gesture recognition method based on multi-feature fusion and fingertip detecting
  • Hand gesture recognition method based on multi-feature fusion and fingertip detecting

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Embodiment

[0076] In this embodiment, a video sequence (640×480 pixels, 30ftps) captured by a Logitech C710 network camera is processed. The video was shot randomly in an indoor scene. The scene contains a complex background, background objects with similar skin colors appear, and there are changes in lighting. The types of gestures include 0, 1, 2, 3, 4, 5, and 8 seven gestures. This embodiment includes the following steps:

[0077] Step 1): Training process: Input all gesture sample images into the training database one by one, select Hu moment feature, defect feature and proportional feature, and use multi-feature fusion feature extraction algorithm to perform support vector machine training on gestures to form a training model ;

[0078] In this embodiment, the training process described in step 1), figure 2 It is a flowchart of the training process, and the specific process is as follows:

[0079] Step 1.1): Training sample preparation:

[0080] The seven categories of gesture ...

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Abstract

The invention discloses a hand gesture recognition method based on multi-feature fusion and fingertip detecting. The method comprises a training process and a recognition process. In the training process, for a complex hand gesture, reasonable hand gesture features are selected, a multi-feature fusion feature extracting algorithm is used, the hand gesture is subjected to support vector machine training, and a training model is formed. In the recognition process, for an input video image sequence, hand gesture detecting is carried out first, then multi-feature extracting and fusion are carried out, and multiple features are input into the support vector machine to obtain a recognition results. Meanwhile, the hand gesture is subjected to fingertip detecting based on defects, through a defect screener, the positions of fingertips of fingers are located, then two-time recognition and detecting results are subjected to synthesized, and the final hand gesture recognition results are obtained. The problem that in a complex scene, the hand gesture recognition rate is not high can be effectively solved, the requirement of real-time performance is met, and the method can be well used in human-machine interaction.

Description

technical field [0001] The invention relates to a gesture recognition method, in particular to a gesture recognition method based on multi-feature fusion and fingertip detection. Background technique [0002] With the development of computers and its application in modern society more and more widely and rapidly, the demand for human-computer interaction technology is also becoming higher and higher in human life. In these interaction technologies, gestures are a natural and human The interaction method of behavior habits has attracted everyone's attention because of its intuitive, convenient and natural characteristics, and it is one of the ideal choices as a new type of human-computer interaction technology. Gesture recognition is one of the most critical steps in the interactive system, and its recognition effect directly affects the communication ability between human and computer. [0003] Combining various researches and practical applications, it can be analyzed that...

Claims

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Application Information

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IPC IPC(8): G06K9/64G06K9/46
Inventor 于慧敏盛亚婷
Owner ZHEJIANG UNIV
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