Antonio Rama

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Face recognition based on 3D techniques is a promising approach since it takes advantage of the additional information provided by depth which makes the whole approach more robust against illumination and pose variations. However, these 3D approaches require the cooperation of the person to acquire accurate 3D data; thus, they are not appropriated for some(More)
The paper presents a novel face detection and tracking algorithm which could be part of human-machine interaction in applications such as intelligent cash machine. The facial feature extraction algorithm is based on discrete approximation of Gabor Transform, called Discrete Gabor Jets (DGJ), evaluated in edge points. DGJ is computed using integral image for(More)
In our previous work we presented a new 2D-3D mixed face recognition scheme called Partial Principal Component Analysis (P 2 CA) [1]. The main contribution of P 2 CA is that it uses 3D data in the training stage but it accepts either 2D or 3D information in the recognition stage. We think that 2D-3D mixed approaches are the next step in face recognition(More)
Recently, 3D face recognition algorithms have outperformed 2D conventional approaches by adding depth data to the problem. However, independently of the nature (2D or 3D) of the approach, the majority of them required the same data format in the test stage than the data used for training the system. This issue represents the main drawback of 3D face(More)
In this paper, we present a flexible system to verify any kind of graphic TV character or symbol in television charts. The proposed approach is very robust towards translations, rotations, changes in scale and illumination variations of the graphic characters. Another important attribute of the proposed system is its speed. The system should be very fast(More)