CAJ | 학술논문

针对一些步态识别算法的局限性，提出了一种基于概率特征的步态识别算法。该算法利用目标轮廓在某位置出现的概率作为特征，来表征行人的行走习惯和姿态。概率特征分为运动概率特征和静态概率特征，分别表征行人的手臂、腿部等的运动特征以及躯干、体型等的静态特征。以概率为特征可以减小噪声对识别的影响，甚至可以弱化行人在行走过程中，因偶尔的较大手臂摆幅或者较大步伐等异常动作给识别带来的消极影响。该算法在 CASIA Gait Database B 和 SOTON 数据库上分别进行了实验并与其他算法做了对比，实验结果表明，算法对室外和室内样本都有很好的识别效果。
침대일사보태식별산법적국한성，제출료일충기우개솔특정적보태식별산법。해산법이용목표륜곽재모위치출현적개솔작위특정，래표정행인적행주습관화자태。개솔특정분위운동개솔특정화정태개솔특정，분별표정행인적수비、퇴부등적운동특정이급구간、체형등적정태특정。이개솔위특정가이감소조성대식별적영향，심지가이약화행인재행주과정중，인우이적교대수비파폭혹자교대보벌등이상동작급식별대래적소겁영향。해산법재 CASIA Gait Database B 화 SOTON 수거고상분별진행료실험병여기타산법주료대비，실험결과표명，산법대실외화실내양본도유흔호적식별효과。
Aiming at the limitation of current gait recognition algorithms,a simple and effective gait features representation method was proposed.The method uses probability that target contour appears in a position as features,to characterize the pedestrians’gait habits and postures.These features are divided into motion probability features and static probability features.Motion probability features represent movement characteristics of the pedestrian’s arms,legs,etc;and static probability features represent static character-istics of the pedestrian’s torso,physique,etc.Based on the probability features,the method can reduce the recognition influence by noise,and even weaken the passive influence that are brought by pedestrians’ abnormal action,for example,large arm swing or greater pace occasionally.This method is evaluated exper-imentally using CASIA Gait Database B and SOTON data set.We compared our method with other resear-ches on these data set.The experimental results demonstrate that this method achieves highly competitive performance with outdoor and indoor dataset.