本文選題：目標檢測 + 手勢分割　； 參考：《南京理工大學》2017年碩士論文

【摘要】：科技進步使人機交互方式朝著更加自然、人性化的方向發(fā)展,傳統(tǒng)的交互方式已不能滿足人們的需求。近年來增強現(xiàn)實和虛擬現(xiàn)實技術(shù)發(fā)展迅速,推動了基于手勢識別的交互技術(shù)的發(fā)展,除此之外,手勢識別在無人機控制、智能家居和手語識別等眾多領(lǐng)域都有廣泛應用,在此背景下,本文對手勢識別算法進行研究,并最終模擬鼠標功能,實現(xiàn)了單目視覺下自然人手的人機交互。本文所實現(xiàn)交互系統(tǒng)由手勢分割、手勢跟蹤、手勢識別、系統(tǒng)實現(xiàn)等模塊組成。在手勢分割模塊中,針對固定閾值的膚色分割方法不能適應實際復雜多變環(huán)境的問題,提出了對人手進行現(xiàn)場膚色建模,并利用此模型進行后續(xù)手勢的分割,實驗結(jié)果顯示能有效地從復雜背.景中分割出手勢。在手勢跟蹤模塊,使用核相關(guān)濾波器跟蹤手勢目標,針目標跟蹤丟失的問題,提出了2種目標再檢測機制。在跟蹤前需要對目標初始化,本文使用支持向量機和滑動窗口檢測人手,但滑動窗口遍歷整幅圖片,帶來巨大的時間開銷,針對人手的運動特性以及背景靜止的特點,提出了檢測之前先利用改進的幀間差分法檢測運動區(qū)域,縮小檢測范圍,該方法使檢測區(qū)域減少到原來的四分之一,顯著提高了檢測速率。在手勢識別模塊,使用傅里葉描述子作為手勢特征,選擇k最近鄰法對靜態(tài)手勢進行識別,在動態(tài)手勢識別中,提出了更簡潔的統(tǒng)計計數(shù)識別方法,此算法完全滿足系統(tǒng)實時性要求。系統(tǒng)實現(xiàn)模塊調(diào)用應用程序接口函數(shù)實現(xiàn)對鼠標的模擬,并利用MFC開發(fā)了一個對話框程序,對手勢識別結(jié)果進行直觀的展示。
[Abstract]:The progress of science and technology makes the human-computer interaction more natural and humanized. The traditional way of interaction can not meet the needs of people. In recent years, the rapid development of augmented reality and virtual reality technology has promoted the development of interactive technology based on gesture recognition. In addition, gesture recognition has been widely used in many fields, such as UAV control, smart home and sign language recognition, etc. Under this background, this paper studies the gesture recognition algorithm, and finally simulates the mouse function, realizes the man-machine interaction of natural hand under monocular vision. The interactive system is composed of gesture segmentation, gesture tracking, gesture recognition, system implementation and so on. In the hand gesture segmentation module, aiming at the problem that the fixed threshold skin color segmentation method can not adapt to the actual complex and changeable environment, a skin color modeling method is proposed for the human hand, and the following hand gesture segmentation is carried out using this model. The experimental results show that it is effective from the complex back. Cut out the gestures in the scene. In the hand gesture tracking module, the kernel correlation filter is used to track the gesture target, and the problem of missing needle target tracking is discussed. Two kinds of target re-detection mechanisms are proposed. It is necessary to initialize the target before tracking. Support vector machine and sliding window are used to detect the human hand, but the sliding window traverses the whole picture, which brings huge time cost, aiming at the movement characteristics of the hand and the static background. Before detection, the improved inter-frame differential method is used to detect the motion area and reduce the detection range. This method reduces the detection area to 1/4, and improves the detection rate significantly. In the gesture recognition module, the Fourier descriptor is used as the gesture feature, and the k-nearest neighbor method is selected to recognize the static gesture. In dynamic gesture recognition, a more concise statistical counting recognition method is proposed. This algorithm fully meets the real-time requirement of the system. The system realizes the simulation of mouse by calling the application program interface function, and develops a dialog program with MFC to show the result of gesture recognition intuitively.
【學位授予單位】：南京理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41

【參考文獻】

相關(guān)期刊論文 前7條

1 路莉;;未來必勝的虛擬現(xiàn)實技術(shù)[J];中國發(fā)明與專利;2016年02期

2 晏浩;張明敏;童晶;潘志庚;;基于Kinect的實時穩(wěn)定的三維多手指跟蹤算法[J];計算機輔助設計與圖形學學報;2013年12期

3 羅元;謝_g;張毅;;基于Kinect傳感器的智能輪椅手勢控制系統(tǒng)的設計與實現(xiàn)[J];機器人;2012年01期

4 湯勇;顧宏斌;周來;;交互系統(tǒng)中實時手勢分割及指尖檢測方法[J];光電工程;2010年07期

5 陶霖密,彭振云,徐光yP;人體的膚色特征[J];軟件學報;2001年07期

6 吳江琴;高文;陳熙霖;;基于數(shù)據(jù)手套輸入的漢語手指字母的識別[J];模式識別與人工智能;1999年01期

7 曾芬芳,李精文,歸寶琪,袁野,陳良貴;手模型分析及手勢識別[J];華東船舶工業(yè)學院學報;1998年05期

，

本文編號：2005281