CVC-07 Virtual-World Pedestrian Dataset 
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      J. Xu, D. Vazquez, A. M. Lopez, J. Marin, D. Ponsa

      Advanced Driver Assistance Systems
      (C) Computer Vision Center 2014

      http://www.cvc.uab.es/adas
      jiaolong@cvc.uab.es

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      References to this pedestrian database should be made to the following article:

      @article{xu:2014,
      title={Learning a Part-based Pedestrian Detector in Virtual World},
      author={J. Xu, D. Vazquez, A. M. Lopez, J. Marin, D. Ponsa},
      journal={IEEE Transactions on Intelligent Transportation Systems},
      year={2014}}

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      Contents: 

        Dataset: 
	        - This dataset contains 2534 pedestrian images and 2000 background images. The pedestrian
	         images have frontal view and left view, which are annotated as 'M' and 'L'. You may flip
	          the pedestrians to get right view examples.
					- An illustration of the dataset can be found [here](http://nbviewer.ipython.org/gist/Jiaolong/9959174)
					- For previous version of virtual-world dataset and other datasets of ADAS group, please
					 visit [our websiet](http://www.cvc.uab.es/adas/site/?q=node/7) 
					- Please consider citing our paper if you use virtual-world dataset in your research:
					
				Annotations:
					- The annotations are saved in: annotation.mat
					- The struct is as follows:
						- filename
						- boxes
						- view
						- parts
						- pLocations
					- The root bounding box is saved in `bboxes`. The format is [x1 y1 x2 y2].
					- Part bounding boxes are in `parts`.
					- `pLocations` record the part center points.
					- Clustered view information:
						- Left view: `L`
						- Frontal/rear view: `M`
	
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      Disclaimer: 

      The data is provided "as is" without express or implied warranty. The database is made freely 
      available to the scientific community under the Creative Commons Attribution-NonCommercial 4.0
      License, i.e., you are free to copy, distribute, transmit and adapt the work, and you must 
      attribute the work in the manner specified by the authors and not use this work for commercial 
      purposes. For more information: http://creativecommons.org/licenses/by-nc/4.0/