Abstract
This paper introduces a new approach for detecting and classifying baggage carried by human in images. The human region is modeled into several components such as head, body, foot and bag. This model uses the location information of baggage relative to human body. Features of each component is extracted. The features are then used to train boosting support vector machine (SVM) and mixture model over component. In experiment, our method achieves promising results in order to build automatic video surveillance system.
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Wahyono, N.g.n., Jo, KH. (2015). Spatial-Based Joint Component Analysis Using Hybrid Boosting Machine for Detecting Human Carrying Baggage. In: Núñez, M., Nguyen, N., Camacho, D., Trawiński, B. (eds) Computational Collective Intelligence. Lecture Notes in Computer Science(), vol 9329. Springer, Cham. https://doi.org/10.1007/978-3-319-24069-5_24
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DOI: https://doi.org/10.1007/978-3-319-24069-5_24
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