Method of Improving Practicability of Indoor Visual Odometry
PENG Tianbo1, WANG Hengsheng1,2, ZENG Bin1
1.College of Mechanical and Electrical Engineering, Central South University, Changsha 410083 2.State Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha 410083
Abstract Aiming at the controversy of the real-time performance, robustness and accuracy in visual odometry, method of improving practicability of indoor visual odometry is put forward to tackle the problem. The corner features of every image in the sequence are obtained using graphics processing unit based oriented FAST and rotated BRIE algorithm and matched using K Nearest neighbor algorithm to reduce the computation time. According to the measurement range of Kinect, points with high measurement error are rejected. To solve the movement of the camera between two frames, the estimation of movement parameters are firstly obtained with efficient perspective-n-point algorithm. Then, they are used as the initial value of Levenberg-Marquedt algorithm to refine the parameters. Random sample consensus is used to reject outliers during the computation of the camera movement. The experimental results show that the proposed method is effective for the accuracy improvement of the motion trajectory calculation.
Fund:Supported by National Basic Research Program of China(No.2013CB035504), Fundamental Research Funds for the Central Universities of Central South University (No.2016zzts313)
About author:: PENG Tianbo, born in 1992, master student. His research interests include machine vision and intelligent robot. WANG Hengsheng(Corresponding author), born in 1963, Ph.D., professor. His research interests include intelligent robot. ZENG Bin, born in 1993, master student. His research interests include machine vision.
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2017, Vol. 30 
