An Architecture for Visual Motion Perception of a Surveillance-based Autonomous Robot

• Type: Article in International Conference Proceedings Book
• Date: 2014

Authors

Pinto, AM (Author) FEUP; Paulo Gomes da Costa (Author) FEUP; António Paulo Moreira (Author) FEUP

Conference proceedings International

Title: 2014 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2014

Pages: 205-211

IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

Espinho, PORTUGAL, MAY 14-15, 2014

Indexing

ISI Web of Knowledge - 5 Citations

Scopus - 8 Citations

Other information

Authenticus ID: P-009-Q8K

DOI: 10.1109/icarsc.2014.6849787

Abstract (EN): This research presents an innovative mobile robotic system designed for active surveillance operations. This mobile robot moves along a rail and is equipped with a monocular camera. Thus, it enhances the surveillance capability when compared to conventional systems (mainly composed by multiple static cameras). In addition, the paper proposes a technique for multi-object tracking called MTMP (Multi-Tracking of Motion Profiles). The MTMP resorts to a formulation based on the Kalman filter and tracks several moving objects using motion profiles. A motion profile is characterized by the dominant flow vector and is computed using the optical flow signature with removal of outliers. A similarity measure based on the Mahalanobis distance is used by the MTMP for associating the moving objects over frames. The experiments conducted in realistic environments have proved that the static perception mode of the proposed robot is able to detect and track multiple moving objects in a short period of time and without using specialized computers. In addition, the MTMP exhibits a good computational performance since it takes less than 5 milliseconds to compute. Therefore, results show that the estimation of motion profiles is suitable for analyzing motion on image sequences.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7