Dana36 Dataset

Object Identification in Surveillance Scenarios


We present a novel dataset for evaluation of object matching and recognition methods in surveillance scenarios. Dataset consists of 23,641 images, depicting 15 persons and nine vehicles. A ground truth data -- the identity of each person or vehicle -- is provided, along with the coordinates of the bounding box in the full camera image. The dataset was acquired from 36 stationary camera views using a variety of surveillance cameras with resolutions ranging from standard VGA to three megapixel. 27 cameras observed the persons and vehicles in an outdoor environment, while the remaining nine observed the same persons indoors. The activity of persons was planned in advance; they drive the cars to the parking lot, exit the cars and walk around the building, through the main entrance, and up the stairs, towards the first floor of the building. The intended use of the dataset is performance evaluation of computer vision methods that aim to (re)identify people and objects from many different viewpoints in different environments and under variable conditions. Due to variety of camera locations, vantage points and resolutions, the dataset provides means to adjust the difficulty of the identification task in a controlled and documented manner. An interface for easy integration into Matlab is provided as well, and the data is complemented by baseline results using the simple color histogram descriptor.


If you use the dataset, please cite:

Vildana Sulić Kenk, Rok Mandeljc, Stanislav Kovačič, Matej Kristan, Melita Hajdinjak, Janez Perš: Visual Re-Identification Across Large, Distributed Camera Networks, Image and Vision Computing, 34(0): 11-26, February 2015. DOI: http://dx.doi.org/10.1016/j.imavis.2014.11.002

Additional code, which comes with the above paper and makes use of this dataset, can be found here.

Download locations:

Note: The length of the dataset is 4.5 GB. It was split into nine parts, and you have to download all parts. It does not matter from which mirror comes which part. To join the parts and decompress the contents, use the free (open source) 7zip utility. In Linux, 7zip appears as the command-line utility, "7z", when it is installed. Please check enclosed CHANGELOG.txt, README.txt and LICENSE.txt after download. The dataset provides Matlab interface in /code subdirectory.

Download location #1: University of Ljubljana, Slovenia

This is the primary download location.



Page last updated: September 2012