【摘要】：機(jī)器視覺、人機(jī)交互如何更好地服務(wù)于人類是當(dāng)今世界的主流研發(fā)問題。伴隨著深度傳感器技術(shù)成熟,機(jī)器視覺得以更加廣泛地應(yīng)用于人類的學(xué)習(xí)生活中,類似于掃地機(jī)器人等智能家居就是人工智能深入到人類生活的體現(xiàn)。其中手勢是一種非常方便高效的交互手段,使用輔助傳感設(shè)備例如數(shù)據(jù)手套、體感技術(shù)等的研發(fā)不斷拓寬了人機(jī)交互的渠道,其中包括對于人手的識別和追蹤的研究。本文對于手勢追蹤的研究與實(shí)現(xiàn),主要是想將此功能應(yīng)用在家庭環(huán)境中,結(jié)合智能家居等設(shè)備,給家庭生活中行動不便的老人或者殘身體有所缺陷的人提供幫助,使手勢追蹤這一功能具體呈現(xiàn)在讓家庭生活中,更好地服務(wù)于人類社會。為了實(shí)現(xiàn)裸手追蹤系統(tǒng),本文主要使用了粒子濾波算法,是對馬爾科夫-蒙特卡洛算法的一種改進(jìn)。不同于普通的追蹤,人體手部顏色相對單一,形狀在不同時刻有所變化,故本文將顏色特征和深度信息相互關(guān)聯(lián)起來使用,結(jié)合人體裸手的形狀變化以及顏色亮度特征,基于深度傳感器對人手進(jìn)行追蹤。本系統(tǒng)使用上一時刻的手勢運(yùn)動速度、位置、形狀、目標(biāo)所占區(qū)域大小等信息,對當(dāng)前時刻的手勢位置進(jìn)行了預(yù)測。在預(yù)測的計(jì)算過程中使用了積分圖,使得前后時刻的運(yùn)動狀態(tài)相差減少,更加有效地使用上一時刻的信息預(yù)測當(dāng)前手勢的位置。本文對系統(tǒng)所實(shí)現(xiàn)的手勢追蹤在不同光照、不同手勢狀態(tài)、遮擋等情況下進(jìn)行了測試,由實(shí)驗(yàn)結(jié)果可知光照情況對手勢識別追蹤有一定的影響,通過對假設(shè)目標(biāo)區(qū)域的空洞填補(bǔ)克服了光照的影響,手勢在相鄰時刻發(fā)生變化、被遮擋的情況下通過積分圖提高效率,可以實(shí)現(xiàn)相鄰時刻變化差異可追蹤,使上一時刻追蹤到的目標(biāo)特征信息應(yīng)用到當(dāng)前時刻的追蹤中,根據(jù)目標(biāo)距離變化、區(qū)域所占像素點(diǎn)個數(shù)差異、速度變化等信息預(yù)測當(dāng)前時刻的目標(biāo)位置,使追蹤結(jié)果更加可靠。故本系統(tǒng)可以在不同狀態(tài)下實(shí)現(xiàn)追蹤,效率較高,結(jié)合在日常生活中用到的手勢,從而可以根據(jù)手部運(yùn)動速度的緩急方向、移動的軌跡分為多種不同的含義,將此系統(tǒng)應(yīng)用于家庭服務(wù)機(jī)器人上,使人機(jī)交互更加便捷。
[Abstract]:Machine vision and human-computer interaction are the main research and development problems in the world. With the maturity of depth sensor technology, machine vision can be more widely used in human learning life. Intelligent home such as floor sweeping robot is the embodiment of artificial intelligence in human life. Gesture is a very convenient and efficient means of interaction. The research and development of auxiliary sensing devices such as data gloves and somatosensory technology has continuously widened the channels of human-computer interaction, including the research on human hand identification and tracking. The purpose of this paper is to apply this function to the home environment, combine with the intelligent home and other devices, to provide help to the old people who are physically disabled or the disabled people in their family life. The function of gesture tracking is presented in the family life and serves the human society better. In order to realize the naked hand tracking system, the particle filter algorithm is mainly used in this paper, which is an improvement to the Markov Monte Carlo algorithm. Different from ordinary tracking, the human hand color is relatively single, and the shape changes at different times. Therefore, the color feature and depth information are used in this paper, combined with the shape change and color luminance feature of human bare hand. The human hand is tracked based on the depth sensor. The system uses the information of the motion speed, position, shape and the size of the target area to predict the gesture position at the current moment. The integral graph is used in the calculation of the prediction, which reduces the difference between the motion state of the time before and after, and more effectively uses the information of the previous moment to predict the position of the current gesture. In this paper, hand gesture tracking is tested under different illumination, different gesture status, occlusion and so on. From the experimental results, it can be seen that illumination has a certain influence on gesture recognition tracking. The effect of illumination is overcome by filling the holes in the hypothetical target area, the gesture changes at the adjacent moment, and the integral image improves the efficiency in the case of occlusion, and the difference between the adjacent moments can be traced. The target feature information which was traced at the last moment is applied to the tracking of the current time, and the target position at the current time is predicted according to the target distance change, the difference in the number of pixels occupied by the region, and the change of the velocity, so that the tracking results are more reliable. Therefore, the system can be tracked in different states, high efficiency, combined with the hand gestures used in daily life, thus can be divided into a variety of different meanings according to the priority direction of the hand movement speed. This system is applied to home service robot, which makes man-machine interaction more convenient.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41;TP212

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