Ms. Christine Dubreu Profile

Christine Dubreu

at FLIR Systems Sàrl

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Proceedings Article | 25 March 2008 Paper

Simulation of video sequences for an accurate evaluation of tracking algorithms on complex scenes

Christine Dubreu, Antoine Manzanera, Eric Bohain

Proceedings Volume 6971, 697109 (2008) https://doi.org/10.1117/12.784262

KEYWORDS: Detection and tracking algorithms, 3D modeling, Video, Databases, Motion models, Algorithm development, Modeling, Computer simulations, Infrared radiation, 3D acquisition

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As target tracking is arousing more and more interest, the necessity to reliably assess tracking algorithms in any conditions is becoming essential. The evaluation of such algorithms requires a database of sequences representative of the whole range of conditions in which the tracking system is likely to operate, together with its associated ground truth. However, building such a database with real sequences, and collecting the associated ground truth appears to be hardly possible and very time-consuming. Therefore, more and more often, synthetic sequences are generated by complex and heavy simulation platforms to evaluate the performance of tracking algorithms. Some methods have also been proposed using simple synthetic sequences generated without such complex simulation platforms. These sequences are generated from a finite number of discriminating parameters, and are statistically representative, as regards these parameters, of real sequences. They are very simple and not photorealistic, but can be reliably used for low-level tracking algorithms evaluation in any operating conditions. The aim of this paper is to assess the reliability of these non-photorealistic synthetic sequences for evaluation of tracking systems on complex-textured objects, and to show how the number of parameters can be increased to synthesize more elaborated scenes and deal with more complex dynamics, including occlusions and three-dimensional deformations.

Proceedings Article | 7 May 2007 Paper

Comprehensive evaluation of tracking systems by non-photorealistic simulation

Christine Dubreu, Antoine Manzanera, Eric Bohain

Proceedings Volume 6569, 65690L (2007) https://doi.org/10.1117/12.720821

KEYWORDS: Detection and tracking algorithms, Algorithm development, Motion models, Video, Computer simulations, Infrared radiation, Video surveillance, Statistical modeling, Databases, Computing systems

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As more and more research effort is drawn into object tracking algorithms, the ability to assess the performance of these algorithms quantitatively has become a fundamental issue in computer vision. Because tracking systems have to operate in widely varying conditions (different weather conditions, background and target characteristics, etc), a large test bed of video sequences is needed in order to obtain a comprehensive evaluation of a tracker across the whole range of its operating conditions. However, it is very unlikely that a dataset of real video sequences representative of the whole range of operating conditions of a tracker together with its ground truth could be obtained, and building a realistic synthetic dataset of such sequences would require costly advanced simulation platforms. In the new evaluation method proposed in this paper, the operational criteria of the tracking system are turned into objective measures and used to generate a synthetic dataset, non-photorealistic, but statistically representative of the whole range of operating conditions. The assessment of an algorithm using our method provides both a quantitative evaluation of the algorithm and the borders of its validity domain. The performance measurement of an algorithm on a synthetic sequence is shown to be consistent with the measurement on a real sequence with the same criteria. The benefit of this approach is twofold: it provides the developer with a way to concentrate on the weaknesses of his algorithm, and helps the system designer to choose the algorithm that best fits the operating constraints.

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