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Content Provider | IEEE Xplore Digital Library |
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Author | Ahmed, E. Jones, M. Marks, T.K. |
Copyright Year | 2015 |
Description | Author affiliation: Univ. of Maryland, College Park, MD, USA (Ahmed, E.) || Mitsubishi Electr. Res. Labs., Cambridge, MA, USA (Jones, M.; Marks, T.K.) |
Abstract | In this work, we propose a method for simultaneously learning features and a corresponding similarity metric for person re-identification. We present a deep convolutional architecture with layers specially designed to address the problem of re-identification. Given a pair of images as input, our network outputs a similarity value indicating whether the two input images depict the same person. Novel elements of our architecture include a layer that computes cross-input neighborhood differences, which capture local relationships between the two input images based on mid-level features from each input image. A high-level summary of the outputs of this layer is computed by a layer of patch summary features, which are then spatially integrated in subsequent layers. Our method significantly outperforms the state of the art on both a large data set (CUHK03) and a medium-sized data set (CUHK01), and is resistant to over-fitting. We also demonstrate that by initially training on an unrelated large data set before fine-tuning on a small target data set, our network can achieve results comparable to the state of the art even on a small data set (VIPeR). |
Starting Page | 3908 |
Ending Page | 3916 |
File Size | 570590 |
Page Count | 9 |
File Format | |
ISSN | 10636919 |
e-ISBN | 9781467369640 |
DOI | 10.1109/CVPR.2015.7299016 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2015-06-07 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Computer architecture Convolution Measurement Machine learning Training Feature extraction Image color analysis |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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