107. STEREO EGO-MOTION ESTIMATION FOR A LONG NOISY SEQUENCE

Department: Electrical & Computer Engineering
Research Institute Affiliation: Center for Wireless Communications (CWC)
Faculty Advisor(s): Truong Q. Nguyen

Primary Student
Name: Haleh Azartash
Email: hazartas@ucsd.edu
Phone: 858-534-5669
Grad Year: 2013

Abstract
In this paper, we propose a novel method to accurately estimate the arbitrary motion of a calibrated stereo rig from a noisy sequence. In the proposed method, a projective camera model is used which is appropriate for scenes where the objects are close to the camera or where there is depth variation in the scene. We propose a feature-based method that estimates large 3D translation and rotation motion of a moving rig. The translational velocity and acceleration and angular velocity of the rig are then estimated using a recursive method. In addition, we account for different motion types such as pure rotation and pure translation in different directions. In our studies, we assume that the motion of the rig is noisy, i.e., the acceleration and velocity of the camera are not perfectly constant. Our experimental results show that we obtain the exact parameters of rotation matrix and translation vector across different test-cases with large and small baselines. For the long sequences, the estimated motion parameters yield the correct results as well.

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