We present a new dataset of annotations for aligning a Point Distribution Model onto the human body. The corresponding research is described in the paper O. Huynh and B.Stanciulescu, “Clustering and Classifying Deformations for Shape Regression applied to the Human Body”, in ISPA 2015. The InriaLHB uses the pedestrian images from the Inria Person Dataset. Annotated shapes correspond to a standing person in front or back view.
Model
The Point Distribution Model employed is defined with the following 29 landmarks :
0 – Top_Left_Head
1 – Top_Right_Head
2 – Bottom_Right_Head
3 – Bottom_Left_Head
4 – Left_Shoulder
5 – Left_External_Elbow
6 – Left_External_Wrist
7 – Left_Internal_Wrist
8 – Left_Internal_Elbow
9 – Left_Axilla
10 – Left_Pelvis
11 – Left_External_Knee
12 – Left_External_Ankle
13 – Left_Foot
14 – Left_Internal_Ankle
15 – Left_Internal_Knee
16 – Center_Pelvis
17 – Right_Internal_Knee
18 – Right_Internal_Ankle
19 – Right_Foot
20 – Right_External_Ankle
21 – Right_External_Knee
22 – Right_Pelvis
23 – Right_Axilla
24 – Right_Internal_Elbow
25 – Right_Internal_Wrist
26 – Right_External_Wrist
27 – Right_External_Elbow
28 – Right_Shoulder
We provide this dataset in two formats :
-Only annotations in csv text files. For this format, the images with the original sizes are used.
-Resized images and annotations with normalized shapes (64×128).
Annotations
Annotations are provided in the CSV format. The separator character is the ‘;’. The first column indicates the reference of the image followed by the coordinates of the landmarks in x and y.
Original images
This format uses the high resolution images of the Inria Person Dataset. Follow this link to download the original images. Annotations may be downloaded from HERE.
Two text files can be found, containing either 408 annotated shapes for training or 129 for testing (same categories as Inria Person Dataset).
Normalized images
These images and annotations are used in the evaluation of the ISPA paper. We define an area in the original images so that the Point Distribution Model after the resizing operation will have a maximal size in width and height of 64×128. Then, we increase this area to fill 50 pixels in the resized images as padding around the shape with a mirror method in each direction. It allows to take into account the area surrounding the person to compute local features etc. Finally, we resize the images octave by octave to avoid blur effect after brutal downsampling.
We also generated the flipped images named as *_a.txt. In total, this dataset contains 816 images and annotations for training and 258 images for testing.
Download the dataset with normalized images : TRAINING SET (62MB), TEST SET (16MB).
Triangulation
The joint triangulation may be found HERE. Indices refer to those indicated above.
Citation
If you use this dataset, please cite our work :
@INPROCEEDINGS{7306027,
author={O. Huynh and B. Stanciulescu},
booktitle={Image and Signal Processing and Analysis (ISPA), 2015 9th International Symposium on},
title={Clustering and classifying deformations for Shape Regression applied to the human body},
year={2015},
pages={25-30},
month={Sept},}
Disclaimer
THIS DATA SET IS PROVIDED “AS IS” AND WITHOUT ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, WITHOUT LIMITATION, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
The images come from the Inria Person Dataset and may contain copyright issues. We take no guarantees or responsibilities arising out of any copyright issue. Use at your own risk.
If you have any questions, contact the authors of the paper Olivier Huynh: olivier[dot]huynh[at]mines-paristech[dot]fr or Bogdan Stanciulescu : bogdan[dot]stanciulescu[at]mines-paristech[dot]fr.
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