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MPII Human Pose
创建来自Hello Dataset / Robert
概要
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Overview

MPII Human Pose dataset is a state of the art benchmark for evaluation of articulated human pose estimation. The dataset includes around 25K images containing over 40K people with annotated body joints. The images were systematically collected using an established taxonomy of every day human activities. Overall the dataset covers 410 human activities and each image is provided with an activity label. Each image was extracted from a YouTube video and provided with preceding and following un-annotated frames. In addition, for the test set we obtained richer annotations including body part occlusions and 3D torso and head orientations.

Data Format

Annotation Description

Annotations are stored in a matlab structure RELEASE having following fields

  • .annolist(imgidx) - annotations for image imgidx
    • .image.name - image filename
    • .annorect(ridx) -body annotations for a person ridx
      • .x1, .y1, .x2, .y2 - coordinates of the head rectangle
      • .scale - person scale w.r.t. 200 px height
      • .objpos - rough human position in the image
      • .annopoints.pointperson-centric body joint annotations
        • .x, .y - coordinates of a joint
        • id - joint id (0 - r ankle, 1 - r knee, 2 - r hip, 3 - l hip, 4 - l knee, 5 - l ankle,6 - pelvis, 7 - thorax, 8 - upper neck, 9 - head top, 10 - r wrist, 11 - r elbow, 12 - r shoulder,13 - l shoulder, 14 - l elbow, 15 - l wrist)
          • is_visible - joint visibility
    • .vidx - video index in video_list
    • .frame_sec - image position in video, in seconds
  • img_train(imgidx) - training/testing image assignment
  • single_person(imgidx) - contains rectangle id ridx of sufficiently separated individuals
  • act(imgidx) activity/category label for image imgidx
    • act_name - activity name
    • cat_name - category name
    • act_id - activity id
  • video_list(videoidx) - specifies video id as is provided by YouTube. To watch video on youtube go to here

Citation

Please use the following citation when referencing the dataset:

@inproceedings{andriluka14cvpr,
               author = {Mykhaylo Andriluka and Leonid Pishchulin and Peter Gehler and Schiele,
Bernt}
               title = {2D Human Pose Estimation: New Benchmark and State of the Art Analysis},
               booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
               year = {2014},
               month = {June}
}

License

BSD-2-Clause

数据集信息
应用场景Pose EstimationAction/Event Detection
标注类型ClassificationKeypoints2D
LicenseBSD-2-Clause
更新时间2021-03-24 22:54:09
数据概要
数据格式Image
数据数量0
文件大小11MB
标注数量0
版权归属方
Max Planck Institute for Informatics
标注方
未知
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