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Opis v angleščini: The INFace (Illumination Normalization techniques for robust Face recognition) toolbox is a collection of Matlab functions intended for researchers working in the filed of face recognition. The toolbox was produced as a byproduct of the research work presented here. It includes implementations of several state-of-the-art photometric normalization techniques and a number of histogram manipulation functions, which can be useful for the task of illumination invariant face recognition.
Opis v angleščini: The PhD (Pretty helpful Development functions for) face recognition toolbox is a collection of Matlab functions and scripts intended to help researchers working in the filed of face recognition. The toolbox was produced as a byproduct of the research work presented here and here. It includes implementations of several state-of-the-art face recognition techniques as well as a number of demo scripts, which can be extremely useful for beginners in the field of face recognition.
Opis v angleščini: Annotated Web Ears (AWE) is a dataset of ear images gathered from the web and in the current form contains 1000 ear images of 100 distinct subjects. The dataset was collected for the goal of studying unconstrained ear recognition and is made publicly available to the community. The dataset comes with a Matlab toolbox dedicated to research in ear recognition. The AWE toolbox implements several state-of-the-art ear recognition techniques and allows for rapid experimentation with the AWE dataset.
Opis v angleščini: AWEx is an extended version of the AWE dataset and contains ear images of more than 330 subjects. The dataset is available upon request. For contact information follow the AWE homepage link.
Opis v angleščini: This version of the AWE dataset contains 1.000 images of 100 persons with the pixel-wise annotations of ear locations. The dataset is available upon request. For contact information follow the AWE homepage link.
Opis v angleščini: SBVPI (Sclera Blood Vessels, Periocular and Iris) is a publicly available dataset primarily intended for sclera and periocular recognition research. It was developed at the Faculty of Computer and Information Science, University of Ljubljana in 2018. It consists of 2399 high quality eye images (3000 x 1700 pixels) belonging to 55 different identities. For each identity at least 32 images with 4 different look directions (straight, left, right, up) are available. Each image is annotated with an ID, gender, eye (left/right), view direction and sample number labels. Unlike other similar datasets, it includes corresponding per-pixels annotations of sclera, sclera vascular structures, iris, pupil and periocular region
Dosegljivo preko: SBVPI homepage