In this paper, we consider the problem of automatic landmark image recognition. Specifically, we identify a fundamental issue that lurks in such applications as modern landmark recognition that arises as a natural consequence of a current state-of-the-art techinque, namely one-versus-all SVM. Then, we provide a unary classification approach that retains much of the benefits of one-versus-all SVM's whilst avoids their shortcomings in the context of landmark recognition tasks. Finally, we provide empirical evidence of the improvements based on our experiments.
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