Real-time Motion Detection for Intelligent Agricultural Vehicle Based on Stereo Vision

Abstract:

A real-time motion detection method based on stereo vision was designed in order to meet the need of precise navigation for intelligent agricultural vehicle. Multi-thread feature points detection was used to improve the efficiency of traditional SIFT algorithm. Normalized comprehensive distance algorithm (NCDA) was used to delete the error matched points. Finally, vehicle motion was calculated by the position variation of feature points in adjacent moment. Experiments showed that the average detection time spent was reduced and computing efficiency was raised up. Error matched points were successfully recognized and erased by NCDA. Measurement errors in one time were less than 0.0045m in x and z axis when the speed was 0.8m/s and image grabbing frequency was 5Hz. Measurement errors in x andzaxis were less than 0.15m when the vehicle kept moving for 10s.