Adjacency Matrix Based Objects Representation for Human Identification in Images

Abstract

In this paper the human object present in images are identified. K-means clustering algorithm is used for segmenting the images and Connected Component Analysis is used as postprocessing step. Initially, templates are created from human posture in idle and various angles. The adjacency matrix is constructed from objects and it is matched with templates. A similarity measure has been proposed for estimating the matching.