CAJ | 학술논문

在无重叠视域的多摄像机监控中，由于不同摄像机的视域差别和视域分离，同一运动目标在不同的视域中的成像可能会非常不同，因此在这种情况下对运动目标进行匹配是一项具有挑战性的工作。提出了一种可以容忍光照的不同，在无重叠视域的多摄像机下进行目标匹配的方法。该方法经过初始聚类和K-means聚类对目标进行主颜色谱的提取，利用EMKM算法改善K-means对初始中心点的依赖性，把提取出来的主颜色谱直方图作为目标的特征，然后利用特征相似度测量来判定任意两个物体之间是否匹配；当无法对某些物体进行准确匹配时，再利用SIFT特征进行下一步匹配。该方法也可以用于有重叠视域的多摄像机目标匹配中，通过与其他匹配方法相结合，提高匹配的准确度。实验结果证实了该方法具有较高的准确度。
재무중첩시역적다섭상궤감공중，유우불동섭상궤적시역차별화시역분리，동일운동목표재불동적시역중적성상가능회비상불동，인차재저충정황하대운동목표진행필배시일항구유도전성적공작。제출료일충가이용인광조적불동，재무중첩시역적다섭상궤하진행목표필배적방법。해방법경과초시취류화K-means취류대목표진행주안색보적제취，이용EMKM산법개선K-means대초시중심점적의뢰성，파제취출래적주안색보직방도작위목표적특정，연후이용특정상사도측량래판정임의량개물체지간시부필배；당무법대모사물체진행준학필배시，재이용SIFT특정진행하일보필배。해방법야가이용우유중첩시역적다섭상궤목표필배중，통과여기타필배방법상결합，제고필배적준학도。실험결과증실료해방법구유교고적준학도。
Due to the difference and the separation of the multiple disjoint camera views, the same object’s appearance in different cameras may be very different, which result in matching moving objects across disjoint camera views is a challenging task. This paper proposes an illumination-tolerant appearance representation, which is capable of matching objects in disjoint camera views. This method is based on a first cluster and K-means cluster to abstract object’s major color spectrum histo-gram, which is introduced to represent a object. Then it uses EMKM to weaken K-means sensitive to the initialization of center values. Finally a feature similarity measurement algorithm is proposed to measure the similarity of any two objects. The paper also introduces SIFT to match objects when can’t tell one from another. Meanwhile, this method can be used in matching objects across overlapping camera views, by means of integrating with other methods to improve the accuracy. Experimental results show the accuracy of the proposed method.