Relevance Feedback in Content-based 3D Object Retrieval A Comparative Study
Abstract
In this paper, we present a comparative study that concerns relevance feedback (RF) algorithms in the context of content-based 3D object retrieval. In this study, we employ RF algorithms which range from query modification and multiple queries to one-class support vector machines (SVM). Furthermore, we employ pseudo relevance feedback (PRF) and show that it can considerably improve the performance of content-based retrieval. Our comparative study is based upon extensive experiments that take into account datasets containing generic as well as CAD models.
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