Adjacency Matrix Based Objects Representation for Human Identification in Images

S. Saravanakumar, A. Vadivel
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引用次数: 1

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 post-processing 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.
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基于邻接矩阵的图像中人体识别对象表示
本文对图像中存在的人体目标进行了识别。采用K-means聚类算法对图像进行分割,后处理步骤采用连通分量分析。最初,模板是由人的姿势在空闲和各种角度创建的。邻接矩阵由对象构造,并与模板匹配。提出了一种相似性测度来估计匹配。
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