Fast and robust tracking of multiple moving objects with a laser range finder

Kluge, Boris; Köhler, Christian; Prassler, Erwin

doi:10.1109/robot.2001.932853

Cited by 87 publications

(54 citation statements)

References 2 publications

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“…Furthermore, J kt is the Jacobian of the corresponding error functions given in (9)- (11). Given this approximation of the error function, we can write…”

Section: Optimizing the Trajectories Of Persons By Means Of Leastmentioning

confidence: 99%

Accurate human motion capture in large areas by combining IMU- and laser-based people tracking

Ziegler

Kretzschmar

Stachniss

et al. 2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-A large number of applications use motion capture systems to track the location and the body posture of people. For instance, the movie industry captures actors to animate virtual characters that perform stunts. Today's tracking systems either operate with statically mounted cameras and thus can be used in confined areas only or rely on inertial sensors that allow for free and large-scale motion but suffer from drift in the pose estimate. This paper presents a novel tracking approach that aims to provide globally aligned full body posture estimates by combining a mobile robot and an inertial motion capture system. In our approach, a mobile robot equipped with a laser scanner is used to anchor the pose estimates of a person given a map of the environment. It uses a particle filter to globally localize a person wearing a motion capture suit and to robustly track the person's position. To obtain a smooth and globally aligned trajectory of the person, we solve a least squares optimization problem formulated from the motion capture suite and tracking data. Our approach has been implemented on a real robot and exhaustively tested. As the experimental evaluation shows, our system is able to provide locally precise and globally aligned estimates of the person's full body posture.

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“…Furthermore, J kt is the Jacobian of the corresponding error functions given in (9)- (11). Given this approximation of the error function, we can write…”

Section: Optimizing the Trajectories Of Persons By Means Of Leastmentioning

confidence: 99%

Accurate human motion capture in large areas by combining IMU- and laser-based people tracking

Ziegler

Kretzschmar

Stachniss

et al. 2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

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show abstract

“…Over the last several years, an increasing number of laser-based people tracking systems have been developed [1][2][3][4][5]. However, all these systems are based on a basic assumption that laser points that belong to the same person can easily be clustered or grouped as one feature point.…”

Section: Introductionmentioning

confidence: 99%

Robust Tracking of Multiple People in Crowds Using Laser Range Scanners

Cui

Zha

Zhao

et al. 2006

18th International Conference on Pattern Recognition (ICPR'06)

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“…They are insensitive to lighting conditions and laser data processing does not consume much time. In [7][8][9][10], one laser scanner is used for multiple people tracking. In our previous research [9], multiple laser scanners are registered to perform a reliable and fast trajectory tracking process.…”

Section: Introductionmentioning

confidence: 99%

Tracking multiple people using laser and vision

Cui

Zha

Zhao³

et al. 2005

2005 IEEE/RSJ International Conference on Intelligent Robots and Systems

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-We present a novel system that aims at reliably detecting and tracking multiple people in an open area. Multiple single-row laser scanners and one video camera are utilized. Feet trajectory tracking based on registration of distance information from multiple laser scanners and visual body region tracking based on color histogram are combined in a Bayesian formulation. Results from tests in a real environment are reported to demonstrate that the system can detect and track multiple people simultaneously with reliable and real-time performance.

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Fast and robust tracking of multiple moving objects with a laser range finder

Cited by 87 publications

References 2 publications

Accurate human motion capture in large areas by combining IMU- and laser-based people tracking

Accurate human motion capture in large areas by combining IMU- and laser-based people tracking

Robust Tracking of Multiple People in Crowds Using Laser Range Scanners

Tracking multiple people using laser and vision

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