一种基于全向视觉的运动物体检测算法

Moving Object Detection Based on Omni-Directional Vision

针对静态摄像头条件下的运动物体,提出一种基于全向图像特性的运动目标检测算法.首先对全向图像进行展开,并应用非线性畸变模型对展开图像校正处理,利用自适应背景建模的方法建立和更新背景模型、去除背景,实现对运动物体的识别与检测.该方法利用全向校正图像分辨率低的特点较好地解决前景提取过程中的噪声和阴影问题.实验表明,该方法对于全向视觉条件下运动物体的检测是快速有效的.

Based on omni-directional image characteristic, an algorithm is proposed to recognize and detect moving object with a static camera. First an omni-directional image is unwrapped through a fast unwrapping algorithm. Then the correction of the unwrapped image is performed based on a nonlinear distortion model. And an adaptive background modeling is built, which is real-time updated. Finally, the foreground is obtained to detect moving object. By the low resolution of the omni-directional correction image, the algorithm effectively solves problems of the noise and the shadow during the abstraction of the foreground. Experimental results show that the proposed algorithm is fast and effective.