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JAAD Behavioral Annotations

NOTE: these annotations are deprecated, please use new annotations in JAAD repo.

This repository contains the behavioral data for select pedestrians in JAAD dataset. Corresponding video sequences and bounding boxes for pedestrians are available from our project site (http://data.nvision2.eecs.yorku.ca/JAAD_dataset/) and github (https://github.com/ykotseruba/JAAD_pedestrian).

In JAAD dataset we identified 686 pedestrians that interact or may potentially interact with the driver. For these pedestrians, in addition to bounding boxes, we provide timestamped behavioral data, behavior attribues as well as scene attributes for each frame.

Behavioral annotations

This data is produced using BORIS 2 (http://www.boris.unito.it) - event logging software for video observations. We provide both the BORIS files in the original tsv text format and xml format.

Each file contains the name of the video file (e.g. video_0001.mp4), independent variables and timestamped observations. The following types of tags and their possible values are defined for each video:

  1. location (indoor/plaza/street) indoor refers to parking, plaza to outdoor parking (e.g. near mall)

  2. weather (cloudy/clear/rain/snow) n/a is set for indoor

  3. time_of_day (daytime/nighttime) n/a for indoor

  4. road_condition (snow/rain/dry) whether the road surface is covered in snow/water or is dry..

The following behaviors are defined for all subjects: clear path, crossing, handwave, look, looking, moving fast, moving slow, walking, nod, signal, slow down, speed up, standing, stopped. Some actions are capitalized to distinguish actions that happen on the road vs actions on the sidewalk (e.g. STANDING means that the pedestrian is standing on the road beyond the curb).

Behavioral data can be downloaded in the original BORIS tsv format and xml.
Below is an example of behavioral data in xml format.

xml
<?xml version="1.0" encoding="utf-8"?>
<video FPS="29.97" filename="video_0001.mp4" id="video_0001" length_sec="20.02" num_frames="600">
   <tags>
      <time_of_day val="daytime"/>
      <weather val="cloudy"/>
      <location val="plaza"/>
      <road_condition val="dry"/>
   </tags>
   <subjects>
      <Driver/>
      <pedestrian1/>
      <pedestrian2/>
   </subjects>
   <actions>
      <Driver>
         <action end_frame="57" end_time="1.9019" id="moving slow" start_frame="1" start_time="0"/>
         <action end_frame="141" end_time="4.7047" id="decelerating" start_frame="58" start_time="1.9353"/>
      </Driver>
      <pedestrian1>
         <action end_frame="364" end_time="12.133" id="standing" start_frame="1" start_time="0.02"/>
         <action end_frame="473" end_time="15.773" id="looking" start_frame="444" start_time="14.8"/>
      </pedestrian1>
      <pedestrian2>
         <action end_frame="70" end_time="2.336" id="walking" start_frame="1" start_time="0.02"/>
      </pedestrian2>
   </actions>
</video>

Xml files can be read in MATLAB using xml2struct.m script available at (https://www.mathworks.com/matlabcentral/fileexchange/28518-xml2struct)

Pedestrian behavior attributes

Behavior attributes for each pedestrian are provided as a text file (pedestrian_attributes.txt).

Each line lists attributes (comma-separated) for a single pedestrian in the following order:
video_id, pedestrian_id, group_size, direction, designated, signalized, gender, age, num_lanes, traffic direction, intersection, crossing

  • video_id, pedestrian_id, gender (male/female and n/a for small children) and age (child/young/adult/senior) are self-explanatory
  • group_size: size of the group that the pedestrian is part of (moving or standing together)
  • direction: indicates whether the pedestrian is moving along the direction of car's movement (LONG), crossing in front of the car (LAT) or standing (n/a)
  • designated: the location where the pedestrian is moving/standing is designated for crossing (D) or non-designated (ND)
  • signalized: the location where the pedestrian is moving/standing is signalized (S), i.e. has a stop sign or traffic lights, or not signalized (NS)
  • num_lanes: number of lanes at the place where the pedestrian is moving/standing
  • traffic direction: OW - one way, TW - two way
  • intersection: yes - crossing at the intersection and no otherwise
  • crossing: 1 - pedestrian completes crossing, 0 - pedestrian does not cross, -1 - no intention of crossing (e.g. waiting at the bus stop, talking to somebody at the curb)

When there are no pedestrians in the video, all attributes are set to "n/a".

Traffic scene elements

We provide traffic_scene_elements.txt file which lists scene elements for each video with corresponding frame numbers.
The text is formatted as follows:
video_id, attr_id: start_frame-end_frame; attr_id: start_frame-end_frame;
Note: if no range is provided, the scene element is visible in all frames of the video.

e.g. video_0005, 1: 1-30; 1: 90-240; 7;

translates to the following : stop sign (1) is visible in frames 1-30 and 90-240, the entire video is filmed in a parking lot (7).

Citing us

If you find our work useful in your research, please consider citing:

@inproceedings{rasouli2017they,
  title={Are They Going to Cross? A Benchmark Dataset and Baseline for Pedestrian Crosswalk Behavior},
  author={Rasouli, Amir and Kotseruba, Iuliia and Tsotsos, John K},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={206--213},
  year={2017}
}

@article{kotseruba2016joint,
  title={Joint attention in autonomous driving (JAAD)},
  author={Kotseruba, Iuliia and Rasouli, Amir and Tsotsos, John K},
  journal={arXiv preprint arXiv:1609.04741},
  year={2016}
}

Authors

  • Amir Rasouli
  • Yulia Kotseruba

Please send email to [email protected] or [email protected] if there are any problems with downloading or using the data.

License

This project is licensed under the MIT License - see the LICENSE file for details

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jaad_behavior's Issues

How are you using BORIS for pedestrian behavior

Just want to know how are you using BORIS for pedestrian behavior? does the bounding boxes data must be the same for BORIS labeling?
What tool do you recommend if BORIS may not be the best tool for pedestrian behavior? Amir mentioned that CVAT better
Please share your ideas and advice.
Thank you

Mislabelling of data

Could someone explain how this is cloudy and not snow? There seem to be many such misnomers. At least two tags should have been added instead. This also seems to be the case with many images, a typical snowy case called clear or rain etc. Please verify.
video_0343 frame 0020

This is video 343 and as per the search on the website it's cloudy

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