Abstract
In this article, we present a component-based visual tracker for mobile platforms with an application to person tracking. The core of the technique is a component-based descriptor that captures the structure and appearance of a target in a flexible way. This descriptor can be learned quickly from a single training image and is easily adaptable to different objects. It is especially well suited to represent humans since they usually do not have a uniform appearance but, due to clothing, consist of different parts with different appearance. We show how this component-based descriptor can be integrated into a visual tracker based on the well known Condensation algorithm. Several person tracking experiments carried out with a mobile robot in different laboratory environments show that the system is able to follow people autonomously and to distinguish individuals. We furthermore illustrate the advantage of our approach compared to other tracking methods.
Similar content being viewed by others
References
Andriluka M, Roth S, Schiele B (2008) People-tracking-by-detection and people-detection-by-tracking. In: IEEE conf on computer vision and pattern recognition (CVPR), 2008
Arras KO, Mozos OM, Burgard W (2007) Using boosted features for the detection of people in 2D range data. In: Proc int’l conf on robotics and automation (ICRA’07), Rome, Italy, 2007
Arras KO, Grzonka S, Luber M, Burgard W (2008) Efficient people tracking in laser range data using a multi-hypothesis leg-tracker with adaptive occlusion probabilities. In: Proc of int’l conf on robotics and automation, 2008
Bellotto N, Hu H (2007) Multisensor data fusion for joint people tracking and identification with a service robot. In: Proc of the IEEE int’l conf on robotics and biomimetics, Sanya, China, 2007
Bennewitz M, Burgard W, Cielniak G, Thrun S (2005) Learning motion patterns of people for compliant robot motion. Int J Robot Res 24
Beuter N, Lohmann O, Schmidt J, Kummert F (2009) Directed attention—a cognitive vision system for a mobile robot. In: 18th IEEE international symposium on robot and human interactive communication, 2009
Bradski GR (1998) Computer vision face tracking for use in a perceptual user interface. Int Technol J
Breglera C, Malik J, Pullen K (2004) Twist based acquisition and tracking of animal and human kinematics. Int J Comput Vis (IJCV) 56(3):179–194
Cheung K, Baker S, Kanade T (2005) Shape-from-silhouette across time part II: applications to human modeling and markerless motion. Int J Comp Vis (IJCV) 63(3):225–245
Comaniciu D, Meer P (2002) Mean shift: a robust approach toward feature space analysis. IEEE Trans Pattern Anal Mach Intell 24(5):603–619
Comaniciu D, Ramesh V, Meer P (2000) Real-time tracking of non-rigid objects using mean shift. In: Proc conf computer vision and pattern recognition, 2000
Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: IEEE conf on computer vision and pattern recognition (CVPR), 2005
Frintrop S (2005) VOCUS: a visual attention system for object detection and goal-directed search. PhD thesis, University of Bonn, Germany, July. Published 2006 in Lecture notes in artificial intelligence (LNAI), vol 3899. Springer, Berlin
Frintrop S, Kessel M (2009) Most salient region tracking. In: Proc of the IEEE int’l conf on robotics and automation (ICRA’09), Kobe, Japan, 2009
Frintrop S, Klodt M, Rome E (2007) A real-time visual attention system using integral images. In: Proc of int’l conf on computer vision systems, 2007
Frintrop S, Königs A, Hoeller F, Schulz D (2009) Visual person tracking using a cognitive observation model. In: ICRA workshop on people detection and tracking, 2009
Gavrila DM, Philomin V (1999) Real-time object detection for smart vehicles. In: Int conference on computer vision (ICCV), 1999
Grabner H, Bischof H (2006) On-line boosting and vision. In: IEEE conference on computer vision and pattern recognition (CVPR), 2006
Hoeller F, Schulz D, Moors M, Schneider FE (2007) Accompanying persons with a mobile robot using motion prediction and probabilistic roadmaps. In: Proc of the int’l conf on robots and systems (IROS). IEEE Press, New York, pp 1260–1265
Isard M, Blake A (1998) Condensation—conditional density propagation for visual tracking. Int J Comput Vis (IJCV) 29(1):5–28
Itti L, Koch C, Niebur E (1998) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell 20(11):1254–1259
Leibe B, Leonardis A, Schiele B (2008) Robust object detection with interleaved categorization and segmentation. Int J Comput Vis 77(1–3):259–289. Special Issue on Learning for Recognition and Recognition for Learning
Mathes T, Piater JH (2006) Robust non-rigid object tracking using point distribution manifolds. In: Proc of the 28th annual symposium of the German Association for Pattern Recognition (DAGM), 2006
Mikic I, Trivedi M, Hunter E, Cosman P (2003) Human body model acquisition and tracking using voxel data. Int J Comput Vis 53(3):199–223
Montemerlo M, Thrun S, Whittaker W (2002) Conditional particle filters for simultaneous mobile robot localization and people-tracking. In: Int’l conf on robotics and automation (ICRA), 2002
Palmer SE (1999) Vision science, photons to phenomenology. The MIT Press, Cambridge
Pérez P, Hue C, Vermaak J, Gangnet M (2002) Color-based probabilistic tracking. In: Proc. of European conf on computer vision, 2002
Pérez P, Vermaak J, Blake A (2004) Data fusion for visual tracking with particles. Proc. IEEE 92(3)
Rohr K (1994) Towards model-based recognition of human movements in image sequences. CVGIP Image Underst 59(1):94–115
Schulz D (2006) A probabilistic exemplar approach to combine laser and vision for person tracking. In: Proc of the int’l conf on robotics science and systems, 2006
Schulz D, Burgard W, Fox D, Cremers AB (2003) People tracking with mobile robots using sample-based joint probabilistic data association filters. Int J Robot Res 22(2)
Song X, Cui J, Zha H, Zhao H (2008) Vision-based multiple interacting targets tracking via on-line supervised learning. In: European conference on computer vision (ECCV), 2008
Tang F, Tao H (2005) Object tracking with dynamic feature graph. In: Proc of the IEEE workshop on VS-PETS, 2005
Taylor G, Kleeman L (2004) A multiple hypothesis walking person tracker with switched dynamic model. In: Conf on robotics and automation (ACRA), 2004
Tiderko A, Bachran T, Hoeller F, Schulz D, Schneider FE (2008) RoSe—a framework for multicast communication via unreliable networks in multi-robot systems. Robot Autonom Syst 56(12):1017–1026
Toyama K, Blake A (2002) Probabilistic tracking with exemplars in a metric space. Int J Comput Vis (IJCV) 48(1):9–19
Urtasun R, Fleet DJ, Fua P (2006) Temporal motion models for monocular and multiview 3d human body tracking. Comput Vis Image Underst (CVIU). Special issue Modeling People
Wu B, Nevatia R (2007) Detection and tracking of multiple, partially occluded humans by Bayesian combination of edgelet based part detectors. Int J Comput Vis (IJCV) 75(2) 75(2):247–266
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Frintrop, S., Königs, A., Hoeller, F. et al. A Component-Based Approach to Visual Person Tracking from a Mobile Platform. Int J of Soc Robotics 2, 53–62 (2010). https://doi.org/10.1007/s12369-009-0035-1
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12369-009-0035-1