Collins, Robert TGross, RalphShi, Jianbo2023-05-222023-05-222002-05-202005-03-16https://repository.upenn.edu/handle/20.500.14332/6128Our goal is to establish a simple baseline method for human identification based on body shape and gait. This baseline recognition method provides a lower bound against which to evaluate more complicated procedures. We present a viewpoint dependent technique based on template matching of body silhouettes. Cyclic gait analysis is performed to extract key frames from a test sequence. These frames are compared to training frames using normalized correlation, and subject classification is performed by nearest neighbor matching among correlation scores. The approach implicitly captures biometric shape cues such as body height, width, and body-part proportions, as well as gait cues such as stride length and amount of arm swing. We evaluate the method on four databases with varying viewing angles, background conditions (indoors and outdoors), walk styles and pixels on target.biometrics (access control)computer visioncorrelation methodsgait analysisimage classificationimage matchingimage motion analysisimage sequencesshape measurementvideo databasesarm swingbackground conditionsbaseline recognition methodbiometric shape cuesbody heightbody shapebody widthbody-part proportionscorrelation scorescyclic gait analysisdatabasesgait cuesindoor conditionskey frame extractionlower boundnearest-neighbor matchingnormalized correlationoutdoor conditionspixelssilhouette-based human identificationstride lengthsubject classificationtemplate matchingtest image sequencetraining framesviewing anglesviewpoint-dependent techniquewalking stylesPresentation