Yet Another Computer Vision Index To Datasets (YACVID) - Details

Stand: 2017-04-26 000000m 02:04:23 - Overview

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Name (Institute + Shorttitle)CASIA Gait Recognition Dataset 
Description (include details on usage, files and paper references)Dataset A (former NLPR Gait Database) was created on Dec. 10, 2001, including 20 persons. Each person has 12 image sequences, 4 sequences for each of the three directions, i.e. parallel, 45 degrees and 90 degrees to the image plane. The length of each sequence is not identical for the variation of the walker抯 speed, but it must ranges from 37 to 127. The size of Dataset A is about 2.2GB and the database includes 19139 images.
The format of the image filename in Dataset A is 憍xx-mm_n-ttt.png�, where
xxx: subject id,
mm: direction,
n: sequence number,
ttt: frame number in a sequence

Dataset B is a large multiview gait database, which is created in January 2005. There are 124 subjects, and the gait data was captured from 11 views. Three variations, namely view angle, clothing and carrying condition changes, are separately considered. Besides the video files, we still provide human silhouettes extracted from video files. The detailed information about Dataset B and an evaluation framework can be found in this paper .
The format of the video filename in Dataset B is 憍xx-mm-nn-ttt.avi�, where
xxx: subject id, from 001 to 124.
mm: walking status, can be 憂m� (normal), 慶l� (in a coat) or 慴g� (with a bag).
nn: sequence number.
ttt: view angle, can be �000′, �018′, �, �180′.

Dataset C was collected by an infrared (thermal) camera in Jul.-Aug. 2005. It contains 153 subjects and takes into account four walking conditions: normal walking, slow walking, fast walking, and normal walking with a bag. The videos were all captured at night.
The format of the video filename in Dataset C is �01xxxmmnn.avi�, where
xxx: subject id, from 001 to 153.
mm: walking status, can be 慺n� (normal), 慺q� (fast walk), 慺s� (slow walk) or 慺b� (with a bag).
nn: sequence number.

Dataset D was collected synchronously by camera and Rscan Footscan in Jul.-Aug. 2009. It contains 88 subjects and takes into account real surveillance scenes and wide age distribution


@inproceedings{szheng_gait_ICIP2011,
author = {Shuai Zheng and Junge Zhang and Kaiqi Huang and Ran He and Tieniu Tan},
title = {Robust View Transformation Model for Gait Recognition},
booktitle = {International Conference on Image Processing(ICIP)},
address = {Brussels, Belgium},
year = {2011}
}

@article{szheng_gaitandfootprint_PR2012,
author = {Shuai Zheng and Kaiqi Huang and Tieniu Tan and Dacheng Tao},
title = {A cascade fusion scheme for gait and cumulative foot pressure image recognition},
journal = {Pattern Recognition},
year = {2012},
volume = {45},
number = {10},
pages={3603-3610},
URL Linkhttp://kylezheng.org/gait-recognition/ 
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Category (SKIPPED) 
Tags (single words, spaced)gait recognition biometry action classification motion human foot pressure 
Last Changed2017-04-26 
Turing (2.12+3.25=?) :-)