This paper formulates the problem of object categorization in the discriminant analysis framework focusing on transforming visual feature data so as to make it conform to the comp...
—Many recognition procedures rely on the consistency of a subset of data features with a hypothesis as the sufficient evidence to the presence of the corresponding object. We ana...
In this paper, we propose a novel feature extraction method for face recognition. This method is based on Discrete Cosine Transform (DCT), Energy Probability (EP), and Linear Disc...
Jean Choi, Yun-Su Chung, Ki-Hyun Kim, Jang-Hee Yoo
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Abstract. The Scale Invariant Feature Transform (SIFT) is an algorithm used to detect and describe scale-, translation- and rotation-invariant local features in images. The origina...