Ground truth image sets, including calibration images, are useful for validation of software - testing the overall ability of the software to provide realistic results with real images, under real-life conditions. Ground truth images can also be modified and used to create quasi-synthetic images for testing susceptibility of algorithms to things like motion blur, image defocus, misregistration and noise.
The synthetic generation of samples make possible experiments with
thousand of subjects (same benchmark data for all researchers) without
any legal concern (avoiding also the time consuming acquisition
procedures). You can find biometric synthetic generation for several
traits: fingerprint, face, handwritting signature, iris, palm
The Sculptures 6k Dataset consists of 6340 images images collected from Flickr by searching for sculptures by Henry Moore and Auguste Rodin.
The dataset is split equally into a train and test set, each
containing 3170 images. For each set 10 different Henry
Moore sculptures are chosen as query objects, and for each
of these objects 7 images and query regions are defined,
thus providing 70 queries for performance evaluation purposes.
The scripted (and unscripted) activities include:
walk, browse, slump, left object, meet, fight, window shop, shop enter, shop exit.
Annotated biological image sets for testing and validation