State-Driven Particle Filter for Multi-person Tracking

Gómez, David; Lerasle, Frédéric; Peña, Antonio M. López

doi:10.1007/978-3-642-33140-4_41

Cited by 6 publications

(1 citation statement)

References 16 publications

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“…The literature presents two main configurations for the application of this type of filters to the MOT task: the decentralized one, which associates a filter to each object, such as the Decentralized Particle Filter (DPF) [44], and the centralized one, where all the objects states constitutes a single representation, like the Tracker Hierarchy [45], and the Reversible Jump Markov Chain Monte Carlo—Particle Filter (RJMCMC) [46].…”

Section: Related Workmentioning

confidence: 99%

An Appearance-Based Tracking Algorithm for Aerial Search and Rescue Purposes

Al-Kaff

Gómez-Silva

Moreno

et al. 2019

Sensors

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The automation of the Wilderness Search and Rescue (WiSAR) task aims for high levels of understanding of various scenery. In addition, working in unfriendly and complex environments may cause a time delay in the operation and consequently put human lives at stake. In order to address this problem, Unmanned Aerial Vehicles (UAVs), which provide potential support to the conventional methods, are used. These vehicles are provided with reliable human detection and tracking algorithms; in order to be able to find and track the bodies of the victims in complex environments, and a robust control system to maintain safe distances from the detected bodies. In this paper, a human detection based on the color and depth data captured from onboard sensors is proposed. Moreover, the proposal of computing data association from the skeleton pose and a visual appearance measurement allows the tracking of multiple people with invariance to the scale, translation and rotation of the point of view with respect to the target objects. The system has been validated with real and simulation experiments, and the obtained results show the ability to track multiple individuals even after long-term disappearances. Furthermore, the simulations present the robustness of the implemented reactive control system as a promising tool for assisting the pilot to perform approaching maneuvers in a safe and smooth manner.

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Section: Related Workmentioning

confidence: 99%

An Appearance-Based Tracking Algorithm for Aerial Search and Rescue Purposes

Al-Kaff

Gómez-Silva

Moreno

et al. 2019

Sensors

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A comparative view on exemplar ‘tracking-by-detection’ approaches

Moussy

Mekonnen

Marion

et al. 2015

2015 12th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)

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Online multi-person tracking via robust collaborative model

Naiel

Ahmad

Swamy

et al. 2014

2014 IEEE International Conference on Image Processing (ICIP)

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The past decade has witnessed significant progress in object detection and tracking in videos. In this paper, we present a model for collaboration between a pre-trained object detector and multiple single object trackers in the particle filter tracking framework. For each frame, we construct an association between the trackers and the detections, and when a tracker is successfully associated to a detection, we treat this detection as the key-sample for this tracker. We present a dual motion model that incorporates the associated detections with the object dynamics. Then, a likelihood function provides different weights for the propagated and the newly created particles, reducing the effect of false positives and missed detections in the tracking process. In addition, we use generative and discriminative appearance models to maximize the appearance variation among the targets. The performance of the proposed algorithm compares favorably with that of the state-of-the-art approaches on three public sequences.

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State-Driven Particle Filter for Multi-person Tracking

Cited by 6 publications

References 16 publications

An Appearance-Based Tracking Algorithm for Aerial Search and Rescue Purposes

An Appearance-Based Tracking Algorithm for Aerial Search and Rescue Purposes

A comparative view on exemplar ‘tracking-by-detection’ approaches

Online multi-person tracking via robust collaborative model

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State-Driven Particle Filter for Multi-person Tracking

Cited by 6 publications

References 16 publications

An Appearance-Based Tracking Algorithm for Aerial Search and Rescue Purposes

An Appearance-Based Tracking Algorithm for Aerial Search and Rescue Purposes

A comparative view on exemplar &#x2018;tracking-by-detection&#x2019; approaches

Online multi-person tracking via robust collaborative model

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Product

Resources

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A comparative view on exemplar ‘tracking-by-detection’ approaches