CAJ | 학술논문

为了有效的克服遮挡问题准确跟踪行人，本文提出了一种通过不断学习新的外观模型来自适应跟踪行人的跟踪算法。该算法首先将颜色不变量特征平面作为根特征来表示初始特征空间；然后将跟踪问题转化为0或1的二进制问题，通过局部最小二乘法（PLS）来对目标外观特征和对应的类型标签进行建模得到前景和背景的模板。随着目标外观的变化，本文利用局部最小二乘法（PLS ）在颜色不变量平面上分析多个外观特征的样本信息，不断的更新模板，从而达到对遮挡具有很好鲁棒性的行人跟踪效果。通过对通用数据集进行试验表明：该算法在颜色暗淡和颜色鲜明的视频图片中都能达到很好的跟踪效果。
위료유효적극복차당문제준학근종행인，본문제출료일충통과불단학습신적외관모형래자괄응근종행인적근종산법。해산법수선장안색불변량특정평면작위근특정래표시초시특정공간；연후장근종문제전화위0혹1적이진제문제，통과국부최소이승법（PLS）래대목표외관특정화대응적류형표첨진행건모득도전경화배경적모판。수착목표외관적변화，본문이용국부최소이승법（PLS ）재안색불변량평면상분석다개외관특정적양본신식，불단적경신모판，종이체도대차당구유흔호로봉성적행인근종효과。통과대통용수거집진행시험표명：해산법재안색암담화안색선명적시빈도편중도능체도흔호적근종효과。
In order to overcome occlusion and track the pedestrian accurately,this paper proposes an object tracking al-gorithm that learns a set of new appearance models for adaptive discriminative object representation.First,we exploit the color invariance as the root feature to obtain the appearance feature.And then,object tracking is taken as a binary classifi-cation problem.The correlation of object appearance and class labels from foreground and background is modeled by the a-nalysis from partial least squares,to generate a low-dimensional discriminative feature.As object appearance varies,we learn and adapt a series of appearance models with PLS analysis to achieve the robustness for tracking.Experiments on gen-eral data sets demonstrate good performance of the proposed tracking algorithm.