Tracking people within groups with RGB-D data

IEEE International Conference on Intelligent Robots and Systems

Volumn , Issue , 2012, Pages 2101-2107

  Munaro, Matteo ^a   Basso, Filippo ^a   Menegatti, Emanuele ^a  

^a UNIVERSITY OF PADOVA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

DATA SETS; HIGH FRAME RATE; INDOOR ENVIRONMENT; MOBILE PLATFORM; NEGATIVE EXAMPLES; STATE-OF-THE-ART PERFORMANCE; SUB-CLUSTERING; THREE-TERM; TRACKING ALGORITHM;

INTELLIGENT SYSTEMS; STATISTICAL TESTS;

SENSORS;

EID: 84872320216     PISSN: 21530858     EISSN: 21530866     Source Type: Conference Proceeding    
DOI: 10.1109/IROS.2012.6385772     Document Type: Conference Paper

References (27)

1. M. Bajracharya, B. Moghaddam, A. Howard, S. Brennan, and L. H. Matthies. A fast stereo-based system for detecting and tracking pedestrians from a moving vehicle. In International Journal of Robotics Research, volume 28, pages 1466-1485, 2009.
2. M. Bansal, S. Jung, B. Matei, J. Eledath, and H. Sawhney. A realtime pedestrian detection system based on structure and appearance classification. In IEEE International Conference on Robotics and Automation (ICRA), pages 903-909. IEEE, 2010.
3. N. Bellotto and H. Hu. Computationally efficient solutions for tracking people with a mobile robot: an experimental evaluation of bayesian filters. Auton. Robots, 28:425-438, May 2010.
4. K. Bernardin and R. Stiefelhagen. Evaluating multiple object tracking performance: the clear mot metrics. J. Image Video Process., 2008:1:1-1:10, January 2008.
5. G. Bradski. The OpenCV Library. Dr. Dobb's Journal of Software Tools, 2000.
6. M. D. Breitenstein, F. Reichlin, B. Leibe, E. Koller-Meier, and L. V. Gool. Robust tracking-by-detection using a detector confidence particle filter. In International Conference on Computer Vision, 2009.
7. A. Carballo, A. Ohya, and S. Yuta. People detection using range and intensity data from multi-layered laser range finders. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 5849 -5854, 2010.
8. W. Choi, C. Pantofaru, and S. Savarese. Detecting and tracking people using an rgb-d camera via multiple detector fusion. In IEEE ICCV Workshops, pages 1076-1083, 2011.
9. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In Computer Vision and Pattern Recognition, 2005., volume 1, pages 886-893, June 2005.
10. A. Ess, B. Leibe, K. Schindler, and L. Van Gool. A mobile vision system for robust multi-person tracking. In IEEE Conference on Computer Vision and Pattern Recognition 2008., pages 1-8, 2008.
11. A. Ess, B. Leibe, K. Schindler, and L. Van Gool. Moving obstacle detection in highly dynamic scenes. In Proc. of ICRA 2009, ICRA'09, pages 4451-4458, Piscataway, NJ, USA, 2009.
12. M. Everingham, L. Gool, C. K. Williams, J. Winn, and A. Zisserman. The pascal visual object classes (voc) challenge. Int. J. Comput. Vision, 88:303-338, June 2010.
13. H. Grabner and H. Bischof. On-line boosting and vision. In Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, pages 260-267, Washington, DC, USA, 2006.
14. E. Hall. The Hidden Dimension. 1966.
15. W. Kim, W. Yibing, I. Ovsiannikov, S. Lee, Y. Park, C. Chung, and E. Fossum. A 1.5Mpixel RGBZ CMOS Image Sensor for Simultaneous Color and Range Image Capture. In IEEE International Solid-State Circuits Conference, San Francisco, USA, February 2012.
16. P. Konstantinova, A. Udvarev, and T. Semerdjiev. A study of a target tracking algorithm using global nearest neighbor approach. In Proc. of the 4th international conference on Computer systems and technologies: e-Learning, pages 290-295, New York, USA, 2003.
17. M. Luber, L. Spinello, and K. O. Arras. People tracking in rgb-d data with on-line boosted target models. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2011.
18. C. Martin, E. Schaffernicht, A. Scheidig, and H.-M. Gross. Multimodal sensor fusion using a probabilistic aggregation scheme for people detection and tracking. Robotics and Autonomous Systems, 54(9):721-728, 2006.
19. D. Mitzel and B. Leibe. Real-time multi-person tracking with detector assisted structure propagation. In IEEE International Conference on Computer Vision Workshops (ICCV Workshops). IEEE, 2011.
20. O. Mozos, R. Kurazume, and T. Hasegawa. Multi-part people detection using 2d range data. Int. Journal of Social Robotics, 2:31-40, 2010.
21. L. E. Navarro-Serment, C. Mertz, and M. Hebert. Pedestrian detection and tracking using three-dimensional ladar data. In FSR, pages 103-112, 2009.
22. R. B. Rusu and S. Cousins. 3D is here: Point Cloud Library (PCL). In Proc. of ICRA 2011, Shanghai, China, May 9-13 2011.
23. J. Satake and J. Miura. Robust stereo-based person detection and tracking for a person following robot. In Workshop on People Detection and Tracking IEEE ICRA, 2009.
24. L. Spinello and K. O. Arras. People detection in rgb-d data. In IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2011.
25. L. Spinello, K. O. Arras, R. Triebel, and R. Siegwart. A layered approach to people detection in 3d range data. In Proc. 24th AAAI Conference on Artificial Intelligence, PGAI Track, Atlanta, USA, 2010.
26. L. Spinello, M. Luber, and K. O. Arras. Tracking people in 3d using a bottom-up top-down people detector. In IEEE International Conference on Robotics and Automation (ICRA'11), Shanghai, 2011.
27. P. Viola and M. Jones. Rapid object detection using a boosted cascade of simple features. In CVPR 2001, volume 1, pages 511-518, 2001.