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CASIA-B

Download URL: http://www.cbsr.ia.ac.cn/GaitDatasetB-silh.zip

  • Original 
    CASIA-B
    001 (subject)
        bg-01 (type)
            000 (view)
                001-bg-01-000-001.png (frame)
                001-bg-01-000-002.png (frame)
                ......
            ......
        ......
    ......
  • Run python datasets/pretreatment.py --input_path CASIA-B --output_path CASIA-B-pkl
  • Processed 
    CASIA-B-pkl
    001 (subject)
        bg-01 (type)
                000 (view)
                    000.pkl (contains all frames)
            ......
        ......
    ......

CASIA-B*

Introduction

CASIA-B* is a re-segmented version of CASIA-B processed by Liang et al. The extra import of CASIA-B* owes to the background subtraction algorithm that CASIA-B uses for generating the silhouette data tends to produce much noise and is outdated for real-world applications nowadays. We use the up-to-date pretreatment strategy to re-segment the raw videos, i.e., the deep pedestrian track and segmentation algorithms. As a result, CASIA-B* consists of the cropped RGB images, binary silhouettes, the height-width ratio of the obtained bounding boxes and the aligned silhouettes. Please refer to GaitEdge for more details. If you need this sub-set, please apply with the instruction mentioned in [http://www.cbsr.ia.ac.cn/english/Gait%20Databases.asp]. In the Email Subject, please mark the specific dataset you need, i.e., Dataset B*.

Data structure

casiab-128-end2end/
    001 (subject)
        bg-01 (type)
                000 (view)
                    000-aligned-sils.pkl (aligned sils, nx64x44)
                    000-ratios.pkl (aspect ratio of bounding boxes, n)
                    000-rgbs.pkl (cropped RGB images, nx3x128x128)
                    000-sils.pkl (binary silhouettes, nx128x128)
            ......
        ......
    ......

How to use

By default, it loads all file directory information like other datasets before training starts. If you need to use some of these data separately, such as aligned-sils, then you can use the data_in_use parameter in data_cfg lexicographically, i.e. data_in_use: [true, false, false, false].