Abstract
In this paper we describe a new method for detecting and tracking multiple persons with a stereo camera. The method is based on the idea of the plan-view map, i.e., the 2D histogram of projected 3D measurements from the camera. It estimates the statistical feature in an optimal window, e.g., a rectangular region, on the histogram, considering stereo measurement error, human breadth, and height. Then, it measures the actual statistical feature in the same window on the input histogram and compares estimated feature with measured one to detect and track persons. Experimental results show that our method can achieve higher performance than a normal plan-view map.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Haritaoglu, I., Harwood, D., Davis, L.S.: W 4 S: A real-time system for detecting and tracking people in \(2 \frac12 D\). In: European Conf. on Computer Vision, pp. 877–892 (1998)
Okada, R., Shirai, Y., Miura, J.: Object tracking based on optical flow and depth. In: IEEE/SICE/RSJ Intl. Conf. on Multisensor Fusion and Integration for Intelligent Systems (1996)
Rehg, J.M., Loughlin, M., Waters, K.: Vision for a smart kiosk. In: Intl. Conf. on Computer Vision and Pattern Recognition, pp. 690–696 (1997)
Darrell, T., Gordon, G., Harville, M., Woodfill, J.: Integrated person tracking using stereo, color, and pattern detection. Intl. Journal of Computer Vision 37, 175–185 (2000)
Beymer, D., Konolige, K.: Real-time tracking of multiple people using stereo. In: Intl. Conf. on Computer Vision (1999)
Beymer, D.: Person counting using stereo. In: Intl. Workshop on Human Motion, pp. 127–133 (2000)
Darrell, T., Demirdjian, D., Checka, N., Felzenszwalb, P.: Plan-view trajectory estimation with dense stereo background models. In: Intl. Conf. on Computer Vision, pp. 628–635 (2001)
Harville, M.: Stereo person tracking with adaptive plan-view templates of height and occupancy statistics. Image Vision Computing 22, 127–142 (2004)
Faugeras, O., Hots, B., Mathieu, H., Vieville, T., Zhang, Z., Fua, P., Theron, E., Moll, L., Berry, G., Vuillemin, J., Bertin, P., Proy, C.: Real time correlation-based stereo: Algorithm, implementations and applications. Technical Report N. 2013, INRIA (1993)
Stauffer, C., Grimson, W.E.L.: Learning patterns of activity using real-time tracking. IEEE Trans. on Pattern Analysis and Machine Intelligence 22, 747–757 (2000)
Rodriguez, J.J., Aggarwal, J.: Stochastic analysis of stereo quantization error. IEEE Trans. on Pattern Analysis and Machine Intelligence 12, 467–470 (1990)
Viola, P., Jones, M.J.: Robust real-time object detection. Technical Report CRL2001/01, COMPAQ Cambridge Research Laboratory (2001)
Isard, M., Blake, A.: Contour tracking by stochastic propagation of conditional density. In: European Conf. on Computer Vision, pp. 343–355 (1996)
Pingali, S., Segen, J.: Performance evaluation of people tracking systems. In: Works. on Application of Computer Vision (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hayashi, K., Hirai, T., Sumi, K., Sasakawa, K. (2006). Multiple-Person Tracking Using a Plan-View Map with Error Estimation. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3851. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612032_37
Download citation
DOI: https://doi.org/10.1007/11612032_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31219-2
Online ISBN: 978-3-540-32433-1
eBook Packages: Computer ScienceComputer Science (R0)