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+from+single-view+RGB+images+is+challenging+due+to+the+absence+of+depth+information+and+potential+occlusions.+Existing+methods+simply+predict+the+body+poses+merely+rely+on+network+training+on+some+indoor+datasets%252C+which+cannot+guarantee+the+rationality+of+the+results+if+some+body+parts+are+invisible+due+to+occlusions+that+appear+easily.+Inspired+by+the+end-effector+localization+task+in+robotics%252C+we+propose+a+kinematics-based+method+that+can+drive+the+joints+of+human+body+to+the+human-object+contact+regions+accurately.+After+an+improved+forward+kinematics+algorithm+is+proposed%252C+the+Multi-Layer+Perceptron+is+introduced+into+the+solution+of+inverse+kinematics+process+to+determine+the+poses+of+joints%252C+which+achieves+precise+results+than+the+commonly-used+numerical+methods+in+robotics.+Besides%252C+a+Contact+Region+Recognition+Network+(CRRNet)+is+also+proposed+to+robustly+determine+the+contact+regions+using+a+single-view+video.+Experimental+results+demonstrate+that+our+method+outperforms+the+state-of-the-art+on+benchmark+BEHAVE.+Additionally%252C+our+approach+shows+good+portability+and+can+be+seamlessly+integrated+into+other+methods+for+optimizations.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.0206c6ac31eac435227a8192850b4a1f%3frik%3d0ipHg1X1PGPl6g%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Comparing+a+Human+to+an+Object&FORM=IRPRST&ck=8979BE15C0D8F7AB68BA4ACAEE015069&selectedIndex=3&itb=0)
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