Abstract
In recent years, there has been increased interest in characterizing and extracting 3D information from video sequences for object tracking and identification. In this paper, we propose a single view-based framework for robust estimation of height and position. In this work, 2D features of a target object is back-projected into the 3D scene space where its coordinate system is given by a rectangular marker. Then the position and height are estimated in the 3D scene space. In addition, geometric error caused by an inaccurate projective mapping is corrected by using geometric constraints provided by the marker. The proposed framework is entirely non-iterative, and therefore is very fast. As the proposed framework uses a single camera, it can be directly embedded into conventional monocular camera-based surveillance/security systems. The accuracy and robustness of the proposed technique are verified on the experimental results of several real video sequences taken from outdoor environments.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Benabdelkader C, Cutler R, Davis L (2002) Person identification using automatic height and stride estimation. In: Proceedings European conference computer vision, 155–158, June 2002
Havasi L, Szlávik Z, Szirányi T (2007) Detection of gait characteristics for scene registration in video surveillance system. IEEE Trans Image Process 16(2):503–510
Liu Z, Sarkar S (2006) Improved gait recognition by gait dynamics normalization. IEEE Trans Pattern Anal Mach Intell 28(6):863–876
Leibowitz D, Criminisi A, Zisserman A (1999) Creating architectural models from images. Proc EuroGraphics’99, 18(3) Sep
Criminisi A, Reid I, Zisserman A (2000) Single view metrology. Int J Comput Vision 40(2):123–148
Criminisi A (2002) Single-view metrology: algorithms and application. In: Proceedings the 24th DAGM symposium on pattern recognition
Lee L, Romano R, Stein G (2000) Monitoring activities from multiple video streams: establishing a common coordinate frame. IEEE Trans Pattern Anal Mach Intell 22(8):758–769 Aug
Hu W, Hu M, Zhou X, Tan T, Lou J, Maybank S (2000) Principal axis-based correspondence between multiple cameras for people tracking. IEEE Trans Pattern Anal Mach Intell 28(4):663–671 Apr
K. Kim and L. Davis, “Multi-camera Tracking and Segmentation of Occluded People on Ground Plane Using Search-Guided Particle Filtering,” Proc. European Conf. Computer Vision, Part III, pp. 98-109, May 2006
Khan S, Shah M (2006) A multiple view approach to tracking people in crowded scenes using a planar homography constraint. In: Proceedings European conference computer vision, Part IV, 133–146, May 2006
Khan S, Shah M (2003) Consistent labeling of tracked objects in multiple cameras with overlapping fields of view. IEEE Trans Pattern Anal Mach Intell 25(10):1355–1361 Oct
Lee SH, Lee SK, Choi JS (2009) Correction of radial distortion using a planar checkerboard pattern and its image. IEEE Trans Consum Electron 55(1):27–33 Feb
Elgammel A, Harwood D, Davis L (2000) Non-parametric model for back ground subtraction. In: Proceedings European conference computer vision, Part II, 751–767, Jun 2000
Zhang Z (2000) Flexible new technique for camera calibration. IEEE Trans Pattern Anal Mach Intell 19(7):1330–1334 Nov
Golub G, Loan C (1996) Matrix computations, 3rd edn. Johns Hopkins Univ Press, Baltimore
Faugeras O (1993) Three-dimensional computer vision. MIT Press, Cambridge
Hartley R, Zisserman A (2003) Multiple view geometry in computer vision. Cambridge University Press, Cambridge
Criminisi A (2001) Accurate visual metrology from single and multiple uncalibrated images. Springer, Berlin
Hu W, Tan T, Wang L, Maybank S (2004) A survey on visual surveillance of object motion and behaviors. IEEE Trans Pattern Anal Mach Intell 34(3):334–353 Aug
Haritaoglu I, Harwood D, Davis L (2000) W4 Real-time surveillance of people. IEEE Trans Pattern Anal Mach Intell 22(8):809–830 Aug
Mckenna S, Jabri S, Duric J, Wechsler H, Rosenfeld A (2000) Tracking groups of people. Comput Vision Image Understand 80:42–56
Liang B, Chen Z, Pears N (2004) Uncalibrated two-view metrology.In: Proceedings international conference pattern recognition, vol. 1. 96–99, Aug 2004
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media B.V.
About this paper
Cite this paper
Park, SW., Kim, TE., Choi, JS. (2012). Robust Estimation of Heights of Moving People Using a Single Camera. In: Kim, K., Ahn, S. (eds) Proceedings of the International Conference on IT Convergence and Security 2011. Lecture Notes in Electrical Engineering, vol 120. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2911-7_36
Download citation
DOI: https://doi.org/10.1007/978-94-007-2911-7_36
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-2910-0
Online ISBN: 978-94-007-2911-7
eBook Packages: EngineeringEngineering (R0)