Multi-Resolution Overlapping Stripes Network for Person Re-Identification

Autor:	Okay, Arda Efe, AlGhamdi, Manal, Westendorp, Robert, Abdel-Mottaleb, Mohamed
Rok vydání:	2019
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	This paper addresses the person re-identification (PReID) problem by combining global and local information at multiple feature resolutions with different loss functions. Many previous studies address this problem using either part-based features or global features. In case of part-based representation, the spatial correlation between these parts is not considered, while global-based representation are not sensitive to spatial variations. This paper presents a part-based model with a multi-resolution network that uses different level of features. The output of the last two conv blocks is then partitioned horizontally and processed in pairs with overlapping stripes to cover the important information that might lie between parts. We use different loss functions to combine local and global information for classification. Experimental results on a benchmark dataset demonstrate that the presented method outperforms the state-of-the-art methods. Comment: 5 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1910.12322 Zobrazit plný text záznamu View this record from Arxiv