为了快速准确地检测并跟踪多目标对象,提出了一种基于全方位视觉的多目标对象跟踪方法.首先采用全方位视觉传感器(ODVS)实时地采集现场360°全景视频图像;接着融合运动历史图像算法(MHI)和运动能量算法(MEI)实现了快速高效的MHoEI(M...为了快速准确地检测并跟踪多目标对象,提出了一种基于全方位视觉的多目标对象跟踪方法.首先采用全方位视觉传感器(ODVS)实时地采集现场360°全景视频图像;接着融合运动历史图像算法(MHI)和运动能量算法(MEI)实现了快速高效的MHoEI(Motion History or Energy Images)自动跟踪算法,对多目标对象进行检测和跟踪;最后,本文采用面向对象技术融合目标对象进行匹配跟踪实验结果表明本文提出的方法能较好地跟踪多目标对象,具有鲁棒性高、运算量小、便于硬件实现、高效等优点.展开更多
Intelligent video surveillance for elderly people living alone using Omni-directional Vision Sensor (ODVS) is an important application in the field of intelligent video surveillance. In this paper, an ODVS is utilized...Intelligent video surveillance for elderly people living alone using Omni-directional Vision Sensor (ODVS) is an important application in the field of intelligent video surveillance. In this paper, an ODVS is utilized to provide a 360° panoramic image for obtaining the real-time situation for the elderly at home. Some algorithms such as motion object detection, motion object tracking, posture detection, behavior analysis are used to implement elderly monitoring. For motion detection and object tracking, a method based on MHoEI(Motion History or Energy Images) is proposed to obtain the trajectory and the minimum bounding rectangle information for the elderly. The posture of the elderly is judged by the aspect ratio of the minimum bounding rectangle. And there are the different aspect ratios in accordance with the different distance between the object and ODVS. In order to obtain activity rhythm and detect variously behavioral abnormality for the elderly, a detection method is proposed using time, space, environment, posture and action to describe, analyze and judge the various behaviors of the elderly in the paper. In addition, the relationship between the panoramic image coordinates and the ground positions is acquired by using ODVS calibration. The experiment result shows that the above algorithm can meet elderly surveillance demand and has a higher recognizable rate.展开更多
文摘为了快速准确地检测并跟踪多目标对象,提出了一种基于全方位视觉的多目标对象跟踪方法.首先采用全方位视觉传感器(ODVS)实时地采集现场360°全景视频图像;接着融合运动历史图像算法(MHI)和运动能量算法(MEI)实现了快速高效的MHoEI(Motion History or Energy Images)自动跟踪算法,对多目标对象进行检测和跟踪;最后,本文采用面向对象技术融合目标对象进行匹配跟踪实验结果表明本文提出的方法能较好地跟踪多目标对象,具有鲁棒性高、运算量小、便于硬件实现、高效等优点.
文摘Intelligent video surveillance for elderly people living alone using Omni-directional Vision Sensor (ODVS) is an important application in the field of intelligent video surveillance. In this paper, an ODVS is utilized to provide a 360° panoramic image for obtaining the real-time situation for the elderly at home. Some algorithms such as motion object detection, motion object tracking, posture detection, behavior analysis are used to implement elderly monitoring. For motion detection and object tracking, a method based on MHoEI(Motion History or Energy Images) is proposed to obtain the trajectory and the minimum bounding rectangle information for the elderly. The posture of the elderly is judged by the aspect ratio of the minimum bounding rectangle. And there are the different aspect ratios in accordance with the different distance between the object and ODVS. In order to obtain activity rhythm and detect variously behavioral abnormality for the elderly, a detection method is proposed using time, space, environment, posture and action to describe, analyze and judge the various behaviors of the elderly in the paper. In addition, the relationship between the panoramic image coordinates and the ground positions is acquired by using ODVS calibration. The experiment result shows that the above algorithm can meet elderly surveillance demand and has a higher recognizable rate.