本文選題：人機(jī)交互 + 手勢(shì)識(shí)別��； 參考：《華中科技大學(xué)》2016年碩士論文

【摘要】：隨著信息技術(shù)的迅猛發(fā)展,計(jì)算機(jī)、智能電視等智能機(jī)器對(duì)于人們的生活愈發(fā)重要。將手勢(shì)引入人機(jī)交互系統(tǒng),使得人們可以和智能設(shè)備通過(guò)定義好的手勢(shì)進(jìn)行交流,這種改變將對(duì)日益趨向電子化的生活帶來(lái)極大的便利。本文先介紹了一種基于手勢(shì)識(shí)別的人機(jī)交互系統(tǒng),系統(tǒng)由視頻圖像采集、視頻圖像分析、智能設(shè)備響應(yīng)等三個(gè)部分構(gòu)成。人臉檢測(cè)、運(yùn)動(dòng)檢測(cè)和手勢(shì)識(shí)別共同組成了系統(tǒng)核心模塊——視頻圖像分析。本文主要對(duì)面向人機(jī)交互的手勢(shì)識(shí)別算法進(jìn)行了研究并提出兩種識(shí)別算法�；谳喞卣鞯淖R(shí)別方法根據(jù)人臉檢測(cè)算法檢測(cè)到的人臉進(jìn)行膚色特征提取;再利用膚色信息和運(yùn)動(dòng)信息完成膚色點(diǎn)檢測(cè)并提取手勢(shì)輪廓;通過(guò)對(duì)輪廓進(jìn)行簡(jiǎn)化和擬合,得到近似手勢(shì)的多邊形以及角度,基于這些信息提取輪廓特征,從而實(shí)現(xiàn)多尺度多角度的手勢(shì)識(shí)別�；谳喞卣鞯淖R(shí)別方法在背景與膚色比較相近的情況下,誤識(shí)率比較高,基于多分類器的手勢(shì)識(shí)別算法克服了這一缺陷。算法主通過(guò)基于分割的跟蹤算法進(jìn)行人手跟蹤,獲取人手的大致輪廓以及位置,通過(guò)這些信息提取直立的人手圖像塊,最后提取該圖像塊的HOG特征,并通過(guò)多個(gè)分類器進(jìn)行手勢(shì)的識(shí)別。算法在復(fù)雜背景膚色相似背景均具有較高識(shí)別率。
[Abstract]:With the rapid development of information technology, computers, intelligent TV and other intelligent machines are becoming more and more important to people's lives.With the introduction of hand gestures into human-computer interaction systems, people can communicate with intelligent devices through well-defined gestures, which will bring great convenience to the increasingly electronic life.This paper first introduces a human-computer interaction system based on gesture recognition, which consists of three parts: video image acquisition, video image analysis and intelligent device response.Face detection, motion detection and gesture recognition constitute the core module of the system-video image analysis.In this paper, the gesture recognition algorithm for human-computer interaction is studied and two recognition algorithms are proposed.The recognition method based on contour feature is used to extract the skin color feature of the face detected by the face detection algorithm; then the skin color information and motion information are used to detect the skin color points and extract the contour of the gesture; the contour is simplified and fitted.The polygon and angle of the approximate gesture are obtained, and the contour features are extracted based on these information, and the multi-scale and multi-angle gesture recognition is realized.The recognition method based on contour features has a high error rate when the background is similar to the skin color. The multi-classifier based gesture recognition algorithm overcomes this defect.The algorithm uses segment-based tracking algorithm to get the rough contour and position of the human hand, extract the vertical human image block through these information, and finally extract the HOG features of the image block.Gestures are recognized by multiple classifiers.The algorithm has high recognition rate for complex background with similar skin color background.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.41

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本文編號(hào)：1741455