Kim Dong-Sun, Kwon Jinsan
Embedded Software Convergence Research Center, Korea Electronics Technology Institute, Saenari-ro 25, Bundang-gu, Seongnam-si, Gyeonggi-do 13509, Korea.
Sensors (Basel). 2015 Dec 25;16(1):23. doi: 10.3390/s16010023.
In the detection of moving objects from vision sources one usually assumes that the scene has been captured by stationary cameras. In case of backing up a vehicle, however, the camera mounted on the vehicle moves according to the vehicle's movement, resulting in ego-motions on the background. This results in mixed motion in the scene, and makes it difficult to distinguish between the target objects and background motions. Without further treatments on the mixed motion, traditional fixed-viewpoint object detection methods will lead to many false-positive detection results. In this paper, we suggest a procedure to be used with the traditional moving object detection methods relaxing the stationary cameras restriction, by introducing additional steps before and after the detection. We also decribe the implementation as a FPGA platform along with the algorithm. The target application of this suggestion is use with a road vehicle's rear-view camera systems.
在从视觉源检测运动物体时,通常假定场景是由固定摄像机捕获的。然而,在车辆倒车的情况下,安装在车辆上的摄像机根据车辆的运动而移动,导致背景上出现自我运动。这会导致场景中出现混合运动,使得难以区分目标物体和背景运动。如果不对混合运动进行进一步处理,传统的固定视点物体检测方法将导致许多误报检测结果。在本文中,我们提出了一种与传统运动物体检测方法一起使用的程序,通过在检测之前和之后引入额外的步骤来放宽固定摄像机的限制。我们还描述了作为FPGA平台以及算法的实现。该建议的目标应用是与道路车辆的后视摄像头系统一起使用。