CAJ | 학술논문

为了降低对象跟踪算法中特征点匹配的复杂度和无用特征点的数量,提高对象提取的精度以及跟踪的速度,提出了一种新的基于帧差特征点和边界点的对象提取、跟踪算法.首先结合形状信息以及自动阀值技术来减少特征点的堆积并提高特征点的利用率,其次从一个新的角度利用帧差技术,不仅有效的将大量的无关特点从跟踪系统中剔除,同时使跟踪范围缩小到一个更加合理高效的区域内.为了让物体的跟踪过程更加精确,通过添加边缘特征点来提高跟踪的鲁棒性.实验结果表明,该算法具有运算量小,精度高,可以处理对象遮挡跟踪问题并具有较强的跟踪鲁棒性的特点.
위료강저대상근종산법중특정점필배적복잡도화무용특정점적수량,제고대상제취적정도이급근종적속도,제출료일충신적기우정차특정점화변계점적대상제취、근종산법.수선결합형상신식이급자동벌치기술래감소특정점적퇴적병제고특정점적이용솔,기차종일개신적각도이용정차기술,불부유효적장대량적무관특점종근종계통중척제,동시사근종범위축소도일개경가합리고효적구역내.위료양물체적근종과정경가정학,통과첨가변연특정점래제고근종적로봉성.실험결과표명,해산법구유운산량소,정도고,가이처리대상차당근종문제병구유교강적근종로봉성적특점.
To reduce the complexity of matching and the amount of useless interest points (IPs) during the tracking system and to enhance the precise of object extracting and object tracking, a new approach for extracting and tracking video stream object based on color interest points and differential pictures is proposed. Firstly, by making use of shape and automatic thresh holding to reduce accumulating and increase operation rate of IPs. Then through a new perspective of using differential pictures, not only large amount of useless IPs are eliminated but also the tracking areas is confined to reasonable bounds. In addition, the edge point added plays an important part in tracking accuracy and robustness. Less computation, more precise, robustness and have the ability to handle occluded objects are demonstrated by experiment on video sequences.