This article describes a new dataset under construction at the Media Integration and Communication Center and the University of Florence. The dataset consists of high-resolution 3D scans of human faces along with several video sequences of varying resolution and zoom level. Each subject is recorded under various scenarios, settings and conditions. This dataset is being constructed specifically to support research on techniques that bridge the gap between 2D, appearance-based recognition techniques, and fully 3D approaches. It is designed to simulate, in a controlled fashion, realistic surveillance conditions and to probe the efficacy of exploiting 3D models in real scenarios.
Florence faces: A dataset supporting 2D/3D face recognition / Bagdanov, Andrew D; Del Bimbo, Alberto; Masi, Iacopo. - ELETTRONICO. - (2012), pp. 1-6. (Intervento presentato al convegno 5th International Symposium on Communications Control and Signal Processing, ISCCSP 2012 tenutosi a Rome, ita nel 2012) [10.1109/ISCCSP.2012.6217829].
Florence faces: A dataset supporting 2D/3D face recognition
BAGDANOV, ANDREW DAVID;DEL BIMBO, ALBERTO;MASI, IACOPO
2012
Abstract
This article describes a new dataset under construction at the Media Integration and Communication Center and the University of Florence. The dataset consists of high-resolution 3D scans of human faces along with several video sequences of varying resolution and zoom level. Each subject is recorded under various scenarios, settings and conditions. This dataset is being constructed specifically to support research on techniques that bridge the gap between 2D, appearance-based recognition techniques, and fully 3D approaches. It is designed to simulate, in a controlled fashion, realistic surveillance conditions and to probe the efficacy of exploiting 3D models in real scenarios.
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