@inproceedings{cff53125e5564863b814325524c5a5d3,
title = "Low resolution gait recognition with high frequency super resolution",
abstract = "Being non-invasive and effective at a distance, recognition suffers from low resolution sequence case. In this paper, we attempt to address the issue through the proposed high frequency super resolution method. First, a group of high resolution training gait images are degenerated for capturing high-frequency information loss. Then the combination of neighbor embedding with interpolation methods is employed for learning and recovering a high resolution test image from low resolution counterpart. Finally, classification is performed based on nearest neighbor classifier. The experiment indicates that the proposed method can effectively improve the accuracy of gait recognition under low resolution case.",
keywords = "Gait energy image, Gait recognition, Super resolution",
author = "Junping Zhang and Yuan Cheng and Changyou Chen",
year = "2008",
doi = "10.1007/978-3-540-89197-0\_49",
language = "English",
isbn = "354089196X",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "533--543",
booktitle = "PRICAI 2008",
note = "10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008 ; Conference date: 15-12-2008 Through 19-12-2008",
}