摘要
介绍了一种在运动相机条件下的基于目标运动与区域灰度信息的运动目标检测算法。采用快速光流估计算法与基于颜色粗糙度的区域分割方法进行目标运动与区域信息的运算,利用待跟踪目标时间与空间信息进行目标定位,降低了目标运动与区域信息估算的复杂度。仿真结果表明,该算法在大多数复杂场景中能够获得良好的目标识别效果。
This paper proposes a novel algorithm for target detection, which is based on motion and region information. A fast optical flow estimation method and a region growing aod merging technique are utilized to estimate the motion vector and the region information of the target respectively. Unlike other algorithms the method makes good use of the motion and region information, as a result the computational complexity of optical flow estimation and region segmentation method decreases distinctly. Simulation results show the algorithm achieves a good performance in most complex outdoor environments.
出处
《计算机工程》
CAS
CSCD
北大核心
2007年第21期205-206,209,共3页
Computer Engineering
基金
中国航天员科研训练中心所长基金资助项目(SJ200502)
关键词
光流估计
区域分割
移动机器人
目标检测
optical flow estimation: region segmentation
mobile robot
target detection