Abstract
The efficient feature matching algorithms are used to improve the quality of object instance search from videos. A trajectory is created based on a sequence of bounding boxes that track the object instance in each frame. The goal is to track the trajectories in high amount of video files. Although the traditional methods of object instance search works well on large image dataset but it fails to produce accurate result in time on videos, which concerns about locating instances of the query object with various changes like color, shape and background. The proposed algorithm was tested with NTU database and it achieves an overall accuracy of 94%.
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Premanand, V., Kumar, D., Arulalan, V. (2020). An Instance Identification Using Randomized Ring Matching Via Score Generation. In: Smys, S., Iliyasu, A.M., Bestak, R., Shi, F. (eds) New Trends in Computational Vision and Bio-inspired Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-41862-5_98
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DOI: https://doi.org/10.1007/978-3-030-41862-5_98
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