Abstract
We propose a method to retrieve the vehicle instance in a massive dataset, that utilizes a cascaded structure to rapidly discard most irrelevant instances. The structure gradually locates the discriminative parts of a vehicle. Rather than focusing on complex and complicated features, we employ a set of prime locating and matching methods successively. During the process, texture features are utilized for localizing the windshield and license plate. Afterwards, vehicle color and type matching are conducted in the located regions of interest. To evaluate the proposed algorithm, we build a dataset comprising approximately 1000 pictures, and experiments show that our algorithm works on the dataset.
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Su, Y., Cuan, B., Zhang, X., Liu, Y. (2016). Rapid Vehicle Retrieval Using a Cascade of Interest Regions. In: Chen, E., Gong, Y., Tie, Y. (eds) Advances in Multimedia Information Processing - PCM 2016. PCM 2016. Lecture Notes in Computer Science(), vol 9917. Springer, Cham. https://doi.org/10.1007/978-3-319-48896-7_13
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DOI: https://doi.org/10.1007/978-3-319-48896-7_13
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