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A gesture recognition method based on multi-feature fusion and fingertip detection

A multi-feature fusion and fingertip detection technology, applied in the field of gesture recognition, can solve the problem of low gesture recognition rate, and achieve the effect of ensuring accuracy, high recognition rate, and small amount of feature calculation.

Active Publication Date: 2018-05-01
ZHEJIANG UNIV
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  • Abstract
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  • 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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  • A gesture recognition method based on multi-feature fusion and fingertip detection
  • A gesture recognition method based on multi-feature fusion and fingertip detection
  • A gesture recognition method based on multi-feature fusion and fingertip detection

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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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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/64G06K9/46
Inventor 于慧敏盛亚婷
Owner ZHEJIANG UNIV
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