A method based on multilayer laserscanner to detect and track pedestrians in urban environment

Gidel, S.; Blanc, Christophe; Chateau, Thierry; Checchin, Paul; Trassoudaine, Laurent

doi:10.1109/ivs.2009.5164270

Cited by 18 publications

(5 citation statements)

References 14 publications

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“…It also copes smoothly and efficiently with groups of people. A “Parzen Window” kernel method is described in Gidel et al () that allows the centralized fusion of information from the four planes of a laser scanner. Additionally, a particle filter with feedback in a laser image is employed for a closer observation of pedestrian random movement dynamics.…”

Section: Review Of Datmo Systemsmentioning

confidence: 99%

Moving object detection with laser scanners

Mertz

Navarro-Serment

MacLachlan

et al. 2012

Journal of Field Robotics

127

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The detection and tracking of moving objects is an essential task in robotics. The CMU‐RI Navlab group has developed such a system that uses a laser scanner as its primary sensor. We will describe our algorithm and its use in several applications. Our system worked successfully on indoor and outdoor platforms and with several different kinds and configurations of two‐dimensional and three‐dimensional laser scanners. The applications vary from collision warning systems, people classification, observing human tracks, and input to a dynamic planner. Several of these systems were evaluated in live field tests and shown to be robust and reliable. © 2012 Wiley Periodicals, Inc.

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Section: Review Of Datmo Systemsmentioning

confidence: 99%

Moving object detection with laser scanners

Mertz

Navarro-Serment

MacLachlan

et al. 2012

Journal of Field Robotics

127

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“…This approach makes it difficult to detect several people accurately in crowded environments, leading to frequent track lost. A typical solution to this problem is to simultaneously detect different body parts of each person, such as legs and torsos, using multilayered LRS [15][16][17].…”

Section: Faculty Of Engineering and Sciencementioning

confidence: 99%

Identification and tracking using laser and vision of people maneuvering in crowded environments

Hashimoto

Konda

Bai

et al. 2010

2010 IEEE International Conference on Systems, Man and Cybernetics

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This paper presents a people tracker that uses a two-layered laser range sensor (LRS) and a fisheye camera. The LRS detects waists and knees of people, and the camera captures color images of torsos of people detected by the LRS. From the data of people's position obtained by the LRS and the color histogram obtained by the camera, heuristic-rule-based and global-nearest-neighbor-based data association can identify multiple people in crowded environments. The identified people are tracked via a model-based tracker; an interacting multiple model estimator is applied to track people maneuvers, such as walking, running, sudden starting/stopping, and sudden turning.Simulation and experimental results show that our people identification and tracking method provides better performance than conventional methods.

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“…Therefore, track lost often occurs. A typical solution to manage with this problem is to simultaneously detect different body parts of a person, such as legs and torso, using multilayered LRS [11][12][13]. Moreover, by allocating multi-LRSs as sensor nodes at different positions in an environment, we can reduce occlusions of people in cluttered environments and improve the tracking performance [4,6,7].…”

Section: Introductionmentioning

confidence: 99%

Laser-based tracking of randomly moving people in crowded environments

Hashimoto

Konda

Bai

et al. 2010

2010 IEEE International Conference on Automation and Logistics

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This paper presents a people tracking system with multiple sensor nodes allocated in an environment. Each sensor node consists of a two-layered laser range sensor (LRS) that detects the positions of waists and knees of people. From the laser images of the people, heuristic-rule-based and global-nearestneighbor (GNN)-based data association can identify a large number of people in crowded environments. The identified people are tracked via a model-based tracker; the interacting multiple model (IMM) estimator is applied to track people moving randomly and flexibly, such as walking, running, going/stopping suddenly, and turning suddenly. Simulation and experimental results validate our people tracking method.

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A method based on multilayer laserscanner to detect and track pedestrians in urban environment

Cited by 18 publications

References 14 publications

Moving object detection with laser scanners

Moving object detection with laser scanners

Identification and tracking using laser and vision of people maneuvering in crowded environments

Laser-based tracking of randomly moving people in crowded environments

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