MPII Cooking 2 Dataset
This site hosts the MPII (Max Planck Institute for Informatics) Cooking Activities dataset 2.0 (short: MPII Cooking 2) as well the corresponding and code [1].
Version 1 has been proposed in [2] and has been extended in [3].
Please contact us if you have questions or would like to get additional features etc.
Download
License
The data is only to be used for scientific purposes and must not be republished other than by the Max Planck Institute for Informatics. The scientific use includes processing the data and showing it in publications and presentations. When using it please cite [1].
Dataset
- Raw data
- videos as avis (29 GB)
- individual videos at http://datasets.d2.mpi-inf.mpg.de/MPII-Cooking-2/videos/sSS-dDD-cam-002.avi
- where SS represents a subject and DD a dish id, e.g. s07-d72
- Video features
- raw dense trajectory, version 1.2 (674 GB)
- Annotations
- Attribue Scores
intermediate attribute scores from SVM (Table 5, IJCV publication)
Please contact Marcus Rohrbach if you need any thing else.
We highly recommend a download manager which allows to continue interrupted downloads, under Linux you could try wget.
FAQ
- The file ‘attributesAnnotations_MPII-Cooking-2.mat’ contains 87 unique activity classes [in matlab after loading attributesAnnotations_MPII-Cooking-2.mat: unique(annos.activity)]. How do I reduce that classes into 67 as you have done in your IJCV paper?
- relevant are only the attributes in annos.attributeMap. You thus get the list of activities with annos.attributeMap(ismember(annos.attributeMap, unique(annos.activity)))
Acknowledgements
The authors would like to thank the annotators for the effort they put into this project, among others:
Amirhossein Baradaranshahroudi, Florin Haque, Seyed Mehdi Khodadad Hosseini, Dragana Majstorovic, and Banafsheh Sadry
Hardware
The dataset was recorded with a camera system from 4D View Solutions.
Help & Contact
If you need any help or have any suggestions feel free to contact Marcus Rohrbach.
We are looking forward to hear from your success of using the dataset.
Feel free to subscribe to our mailing list to get updates (cookingactivities-join@lists.mpi-inf.mpg.de).
Related datasets of our group
- MPII Cooking Activities (a subset focusing on detecting fine-grained activities)
- Saarbrücken Corpus of Textually Annotated Cooking Scenes (short: TACoS) textual descriptions for MPII Cooking Composite Activities
- MPII Multi-Kinect Dataset: Multi-view kinect object classification, recorded in the same kitchen
References
[1] Recognizing Fine-Grained and Composite Activities using Hand-Centric Features and Script Data, M. Rohrbach, A. Rohrbach, M. Regneri, S. Amin, M. Andriluka, M. Pinkal, B. Schiele, IJCV 2015
@article{rohrbach15ijcv,
year={2015},
journal={International Journal of Computer Vision},
title={Recognizing Fine-Grained and Composite Activities Using Hand-Centric Features and Script Data},
author={Rohrbach, Marcus and Rohrbach, Anna and Regneri, Michaela and Amin, Sikandar and Andriluka, Mykhaylo and Pinkal, Manfred and Schiele, Bernt},
issn={0920-5691}, doi={10.1007/s11263-015-0851-8}, url={http://dx.doi.org/10.1007/s11263-015-0851-8}, publisher={Springer US}, pages={1-28}, } @arXiv: 1502.06648, 2015
[2] Script Data for Attribute-based Recognition of Composite Activities, M. Rohrbach, M. Regneri, M. Andriluka, S. Amin, M. Pinkal and B. Schiele, European Conference on Computer Vision (ECCV), October, (2012)
[3] A Database for Fine Grained Activity Detection of Cooking Activities, M. Rohrbach, S. Amin, M. Andriluka and B. Schiele, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June, (2012)