The two-dimensional Principal Component Analysis (2DPCA) is a robust method in face recognition. Much recent research shows that the 2DPCA is more reliable than the well-known PCA ...
The main achievement of this work is the development of a new face recognition approach called Partial Principal Component Analysis (P2 CA), which exploits the novel concept of us...
Antonio Rama, Francesc Tarres, Davide Onofrio, Ste...
We present a novel technique for motion-based recognition of individual gaits in monocular sequences. Recent work has suggested that the image self-similarity plot of a moving per...
Chiraz BenAbdelkader, Ross Cutler, Harsh Nanda, La...
Abstract. Active Shape Models are commonly used to recognize and locate different aspects of known rigid objects. However, they require an off-line learning stage, such that the ex...
Michael Fussenegger, Peter M. Roth, Horst Bischof,...
In this paper we investigate the usage of random ortho-projections in the compression of sparse feature vectors. The study is carried out by evaluating the compressed features in ...