Locally Important Pattern Clustering Code for Pedestrian Classification

Abstract

In this letter, a local pattern coding scheme is proposed to reduce the dimensionality of feature vectors in the local ternary pattern. The proposed method encodes the ternary patterns into a binary pattern by clustering similar ternary patterns. The experimental results show that the proposed method outperforms the previous methods. Copyright © 2015 The Institute of Electronics, Information and Communication Engineers.