Paper
19 November 2012 Object tracking in the video sequence based on the automatic selection of the appropriate coordinate estimation method
Boris Alpatov, Pavel Babayan, Sergey Smirnov
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Abstract
In this paper we propose an object tracking approach that includes the selection of the appropriate coordinate estimation method from the set of base methods: cross-correlation, statistical segmentation, methods based on spatial and spatiotemporal filtering. The tracking performance of the base methods is estimated by means of the several parameters (performance features) that describe the reliability of tracking. The features are invariant to the changes of the mean brightness, contrast, scale and rotation. The comparison of the performance of the methods is based on the binary performance characteristic that describes the tracking in the terms of work/not work. The proposed object tracking algorithm is implemented in five steps which are carried out on each frame: the calculation of the performance feature for each base coordinate estimation method, the calculation of the binary performance characteristic for each method, the selection of the appropriate method, the estimation of the object coordinates using the selected method, the correction of the tracking process performed by other methods. The algorithm shows a good tracking performance during the variations of the observation conditions. In most cases it comprises the main advantages of each of the source methods.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Boris Alpatov, Pavel Babayan, and Sergey Smirnov "Object tracking in the video sequence based on the automatic selection of the appropriate coordinate estimation method", Proc. SPIE 8542, Electro-Optical Remote Sensing, Photonic Technologies, and Applications VI, 85420N (19 November 2012); https://doi.org/10.1117/12.974603
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Cited by 1 scholarly publication.
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KEYWORDS
Detection and tracking algorithms

Image processing algorithms and systems

Statistical analysis

Spatial filters

Binary data

Image processing

Automatic tracking

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