A Low Complexity and High Accuracy Algorithm of Gesture Extraction Based on Binocular Stereo Vision

LV Jun-hong; REN Yi-yi; XIE Xiang; LI Guo-lin

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A Low Complexity and High Accuracy Algorithm of Gesture Extraction Based on Binocular Stereo Vision

更新时间：2026-09-04

- A Low Complexity and High Accuracy Algorithm of Gesture Extraction Based on Binocular Stereo Vision
- Vol. 31, Issue 1, Pages: 120-123(2014)
- 作者机构：
  
  1. 1 清华大学微电子学研究所,北京,100084
  2. 2 清华大学电子工程系,北京,100084
- 作者简介：
- 基金信息：
- DOI：
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- Published：2014
- 稿件说明：
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吕俊宏, 任仡奕, 谢翔, 李国林. 基于双目视觉的低复杂度高准确度手势提取算法[J]. 微电子学与计算机, 2014, 31(1): 120-123.

LV Jun-hong, REN Yi-yi, XIE Xiang, et al. A Low Complexity and High Accuracy Algorithm of Gesture Extraction Based on Binocular Stereo Vision[J]. 2014, 31(1): 120-123.
吕俊宏, 任仡奕, 谢翔, 李国林. 基于双目视觉的低复杂度高准确度手势提取算法[J]. 微电子学与计算机, 2014, 31(1): 120-123. DOI：

LV Jun-hong, REN Yi-yi, XIE Xiang, et al. A Low Complexity and High Accuracy Algorithm of Gesture Extraction Based on Binocular Stereo Vision[J]. 2014, 31(1): 120-123. DOI：

摘要

为满足实时人机交互的需求，解决在不同光照、不同背景下，与肤色无关的手势提取问题，提出了一种低复杂度、高准确度、适合硬件实现的手势提取算法.该算法对双目图像基于逐行扫描的机制提取手势.首先检测边缘，由边缘对图像形成分割，获得手势轮廓，随后通过匹配提取出手势，最后消除背景噪声的影响，获得准确的手势.实验采用两个相同型号的网络摄像头在室内光照条件下采集图像.结果表明，该方法在复杂背景中能够快速准确地提取出各种手势，相比传统的基于肤色的手势提取方法干扰更少.

Abstract

A gesture extraction algorithm with low complexity and high accuracy is presented in this paper.This algorithm meets the needs of real-time human-computer interaction

solves the problem of gesture extraction which has nothing to do with skin color in different light conditions and different backgrounds.And it is suitable for hardware implementation.The algorithm extracts the gesture based on the row-by-row basis in binocular images.Firstly

edges in both images are detected and images are segmented by the edges so that the gesture contour can be obtained.Secondly

the gesture is extracted by a matching algorithm.Finally

background noise are eliminated and accurate gesture comes out.In this paper

the binocular images are captured by two same web cameras in the indoor lighting conditions.The experimental results show that the algorithm is able to extract various gestures quickly and accurately in complex background

and is more robust compared to traditional gesture extraction algorithm based on skin color.

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Related Author

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Related Institution

1 Institute of Microelectronics, Tsinghua University

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