UIUC Image Database : Car Detection

UIUC Image Database for Car Detection

Data

This database contains images of side views of cars for use in evaluating object detection algorithms. The images were collected at UIUC by Shivani Agarwal, Aatif Awan and Dan Roth, and were used in the experiments reported in [1], [2].

The download package contains the following:

1050 training images (550 car and 500 non-car images)
170 single-scale test images, containing 200 cars at roughly the same scale as in the training images
108 multi-scale test images, containing 139 cars at various scales
Evaluation files
README file

The images are all grey-scale and are available in raw PGM format. The evaluation files provide a standardized method for evaluating different algorithms. The evaluation scheme is the same as that used in [1] (note that this differs from the evaluation scheme used in [2]; see [1] for details). Instructions for using the evaluation routine are provided in the README file; this file can also be viewed here.

The gzipped download file is around 7 MB; the unzipped data takes up around 14 MB.

Download

Related Publications

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[1]	Shivani Agarwal, Aatif Awan, and Dan Roth, Learning to detect objects in images via a sparse, part-based representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(11):1475-1490, 2004.
[2]	Shivani Agarwal and Dan Roth, Learning a sparse representation for object detection. In Proceedings of the Seventh European Conference on Computer Vision, Part IV, pages 113-130, Copenhagen, Denmark, 2002.

Acknowledgements

This research, including the collection of this database, was supported by NSF grants ITR IIS 00-85980 and ITR IIS 00-85836.

Questions or comments can be directed to sagarwal@cs.uiuc.edu