특이점 가중치 기반 PLSA를 이용한 객체 범주화 = Object Categorization Using PLSA Based on Weighting

다국어 초록 (Multilingual Abstract)

In this paper we propose a new approach that recognizes the similar categories by weighting distinctive features. The approach is based on the PLSA that is one of the effective methods for the object categorization. PLSA is introduced from the information retrieval of text domain. PLSA, unsupervised method, shows impressive performance of category recognition. However, it shows relatively low performance for the similar categories which have the analog distribution of the features. In this paper, we consider the effective object categorization for the similar categories by weighting the mainly distinctive features. We present that the proposed algorithm, weighted PLSA, recognizes similar categories. Our method shows better results than the standard PLSA.

참고문헌 (Reference)

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