Realtime Multibody Visual SLAM with a Smoothly Moving Monocular Camera

Abhijit Kundu, K M. Krishna and C. V. Jawahar. Realtime Multibody Visual SLAM with a Smoothly Moving Monocular Camera. IEEE International Conference on Computer Vision (ICCV), 2011. (Oral)

Paper: pdf.gif bibtex.gif
Supplementary: pdf.gif(Additional Results) vidMSsmall.jpg (Video)

Abstract: This paper presents a realtime, incremental multibody visual SLAM system that allows choosing between full 3D reconstruction or simply tracking of the moving objects. Motion reconstruction of dynamic points or objects from a monocular camera is considered very hard due to well known problems of observability. We attempt to solve the problem with a Bearing only Tracking (BOT) and by integrating multiple cues to avoid observability issues. The BOT is accomplished through a particle filter, and by integrating multiple cues from the reconstruction pipeline. With the help of these cues, many real world scenarios which are considered unobservable with a monocular camera is solved to reasonable accuracy. This enables building of a unified dynamic 3D map of scenes involving multiple moving objects. Tracking and reconstruction is preceded by motion segmentation and detection which makes use of efficient geometric constraints to avoid difficult degenerate motions, where objects move in the epipolar plane. Results reported on multiple challenging real world image sequences verify the efficacy of the proposed framework.

We used datasets from the following sources: Correction: Reference [2] is missing in the main paper.

[1] G. Brostow, J. Fauqueur, and R. Cipolla. Semantic object classes in video: A high-definition ground truth database. PRL, 30(2):88–97, 2009.
[2] A. Comport, E. Malis, and P. Rives. Real-time Quadrifocal Visual Odometry. IJRR, 29(2-3):245, 2010.
[3] M. Smith, I. Baldwin, W. Churchill, R. Paul, and P. Newman. The new college vision and laser data set. IJRR, 28(5):595, 2009.
[4] S. Wangsirpitak and D. Murray. Avoiding moving outliers in visual slam by tracking moving objects. In ICRA, 2009.