Abstract
In this paper we introduce a novel image descriptor, LBP-gist, suitable for real time loop closure detection. As the name suggests, the proposed method builds on two popular image analysis techniques: the gist feature, which has been used in holistic scene description and the LBP operator, originally designed for texture classification. The combination of the two methods gives rise to a very fast computing feature which is shown to be competitive to the state-of-the-art loop closure detection. Fast image search is achieved via Winner Take All Hashing, a simple method for image retrieval that exploits the descriptive power of rank-correlation measures. Two modifications of this method are proposed, to improve its selectivity. The performance of LBP-gist and the hashing strategy is demonstrated on two outdoor datasets.
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Campos, F.M., Correia, L., Calado, J.M.F. (2013). Loop Closure Detection with a Holistic Image Feature. In: Correia, L., Reis, L.P., Cascalho, J. (eds) Progress in Artificial Intelligence. EPIA 2013. Lecture Notes in Computer Science(), vol 8154. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40669-0_22
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DOI: https://doi.org/10.1007/978-3-642-40669-0_22
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