Recursive camera-motion estimation with the trifocal tensor.
In this paper, an innovative extended Kalman filter (EKF) algorithm for pose tracking using the trifocal tensor is proposed. In the EKF, a constant-velocity motion model is used as the dynamic system, and the trifocal-tensor constraint is incorporated into the measurement model. The proposed method has the advantages of those structure- and-motion-based approaches in that the pose sequence can be computed with no prior information on the scene structure. It also has the strengths of those model-based algorithms in which no updating of the three-dimensional (3-D) structure is necessary in the computation. This results in a stable, accurate, and efficient algorithm. Experimental results show that the proposed approach outperformed other existing EKFs that tackle the same problem. An extension to the pose-tracking algorithm has been made to demonstrate the application of the trifocal constraint to fast recursive 3-D structure recovery.
Yu
Ying Kin
YK
Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong. ykyu@cse.cuhk.edu.hk
Wong
Kin Hong
KH
Chang
Michael Ming Yuen
MM
Or
Siu Hang
SH
D000465:Algorithms; D001185:Artificial Intelligence; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009038:Motion; D010363:Pattern Recognition, Automated / Q000379:methods*; D010780:Photogrammetry / Q000379:methods*; D012815:Signal Processing, Computer-Assisted