Object recognition under severe occlusions with a hidden Markov model approach

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• 作者：F.A. Guerrero-Peñ ; a ; ^{fagp@cin.ufpe.br} ; G.C. Vasconcelos
• 关键词：Severe occluded ; Hidden Markov model ; Wavelet transform ; Object recognition
• 刊名：Pattern Recognition Letters
• 出版年：2017
• 出版时间：15 January 2017
• 年：2017
• 卷：86
• 期：Complete
• 页码：68-75
• 全文大小：1610 K
• 卷排序：86

文摘

The main contributions of this paper are: A new method for recognition of non-deformable severe occluded objects. Local shape descriptor from the wavelet coefficients of the tangent angle signature. Most likely object retrieval based on an ensemble of Hidden Markov Models. Two new area restrictions for consistency checking between hypotheses and occlusion.