Object categorisations using templates constructed from multi-scale line and edge representations

Object categorisation is linked to detection, segregation and recognition. In the visual system, these processes are achieved in the ventral \what"and dorsal \where"pathways [3], with bottom-up feature extractions in areas V1, V2, V4 and IT (what) in parallel with top-down attention from PP via MT to V2 and V1 (where). The latter is steered by object templates in memory, i.e. in prefrontal cortex with a what component in PF46v and a where component in PF46d.

Face normalization using multi-scale cortical keypoints

Empirical studies concerning face recognition suggest that faces may be stored in memory by a few canonical representations. Models of visual perception are based on image representations in cortical area V1 and beyond, which contain many cell layers for feature extractions. Simple, complex and end-stopped cells tuned to different spatial frequencies (scales) and/or orientations provide input for line, edge and keypoint detection. This yields a rich, multi-scale object representation that can be stored in memory in order to identify objects. The multi-scale, keypoint-based saliency maps for Focus-of-Attention can be explored to obtain face detection and normalization, after which face recognition can be achieved using the line/edge representation. In this paper, we focus only on face normalization, showing that multi-scale keypoints can be used to construct canonical representations of faces in memory.

Study of the water consuption of the international tourism sector in the costal zone of southwest Europe

Dissertação de Mestrado, Gestão da Água e da Costa, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2009

Purificação e caracterização de proteínas Gla nos modelos peixe e mamífero

Dissertação de Mestrado, Biologia Molecular e Microbiana, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2010