Motion Estimation Based on Two Corresponding Points and Angular Deviation Optimization

• Published in: IEEE transactions on industrial electronics (1982) 2017-11, Vol.64 (11), p.8598-8606
• Main Authors: Hoang, Van-Dung, Le, My-Ha, Jo, Kang-Hyun
• Format: Article
• Language: English
• Subjects: Automotive parts; Bundle adjustment; Cameras; Computing time; Constraint modelling; Geometric constraints; Geometry; Motion estimation; Motion simulation; nonholonomic constraint; Optimization; Parameters; quasiconvex optimization; Roads; Steering; Three dimensional motion; Three-dimensional displays; Transmission line matrix methods; Vision; visual odometry (VO); Visualization
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2017.2703891

Recently, there have been several studies on vision-based motion estimation under a supposition that planar motion follows a nonholonomic constraint. This allows reducing computational time. However, the vehicle motion in an outdoor environment does not accept this assumption. This paper presents a method for estimating the vision-based 3-D motion of a vehicle with several parts as follows. First, the Ackermann steering model is applied to reduce constraint parameters of the 3-D motion. In difference to the previous contribution, the proposed approach requires only two corresponding points of consecutive images to estimate the vehicle motion. Second, motion parameters are extracted based on a closed-form solution on geometric constraints. Third, the estimation approach applies the bundle adjustment-based quasiconvex optimization. This task aims to take into account advantage of omnidirectional vision-based features for reducing errors. The omnidirectional vision supports for landmarks tracking in long travel and large rotation, which is appropriate for a bundle adjustment technique. Evaluated results show that the proposed method is applicable in the practical condition of outdoor environments.