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In this paper, we present an efficient concept detection system based on a novel bag of words extraction method and sparse ensemble learning. The presented system can efficiently build the concept detectors upon large scale image dataset, and achieve real-time concept detection on unseen images with the state-of-the-arts accuracy. To do so, we first develop an efficient bag of visual words (BoW) construction...
Recently, using large visual vocabulary or codebooks to quantize and partition the set of local feature descriptors into large set of disjoint subsets termed visual words (or large visual words) has become an important research topic in solving many computer vision problems including near duplicate image retrieval, object retrieval, etc. Generally, large visual words means a heavy burden on the cost...
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