Real-Time Object Recognition Based on Cortical Multi-scale Keypoints

• Autor(es): Terzic, Kasim ; Rodrigues, J. M. F. ; du Buf, J. M. H.
• Data: 2013
• Identificador Persistente: http://hdl.handle.net/10400.1/3374
• Origem: Sapientia - Universidade do Algarve
• Assunto(s): Pattern Recognition; Computer imaging; Vision; Computer Graphics; Artificial Intelligence
• Tipo de Documento: Parte ou capítulo de livro
• Idioma: Inglês

Descrição

In recent years, a large number of impressive object categorisation algorithms have surfaced, both computational and biologically motivated. While results on standardised benchmarks are impressive, very few of the best-performing algorithms took run-time performance into account, rendering most of them useless for real-time active vision scenarios such as cognitive robots. In this paper, we combine cortical keypoints based on primate area V1 with a state-of-the-art nearest neighbour classifier, and show that such a system can approach state-of-the-art categorisation performance while meeting the real-time constraint.