The use of local features in computer vision has shown to be promising. Local features have several advantages including invariance to image transformations, independence of the ba...
Sparse coding which encodes the original signal in a sparse signal space, has shown its state-of-the-art performance in the visual codebook generation and feature quantization pro...
Existing action recognition approaches mainly rely on the discriminative power of individual local descriptors extracted from spatio-temporal interest points (STIP), while the geo...
Anh Phuong Ta, Christian Wolf, Guillaume Lavoue, A...
— This paper presents a case study of learning to select behavioral primitives and generate subgoals from observation and practice. Our approach uses local features to generalize...
Darrin C. Bentivegna, Christopher G. Atkeson, Gord...
In this paper, we presented an image search service for mobile users. It can be used to acquire related information by taking and sending pictures to the server, for example, gett...
In the literature of psychophysics and neurophysiology, many studies have shown that both global and local features are crucial for face representation and recognition. This paper...
This paper introduces an edge-based object recognition method that is robust with respect to clutter, occlusion and object deformations. The method combines the use of local featu...
This paper presents an unsupervised learning approach to video-based face recognition that does not make any assumptions about the pose, expressions or prior localization of landm...
Different types of visual object categories can be found in real-world applications. Some categories are very heterogeneous in terms of local features (broad categories) while oth...
Recent developments in computer vision have shown that local features can provide efficient representations suitable for robust object recognition. Support Vector Machines have be...
Christian Wallraven, Barbara Caputo, Arnulf B. A. ...