The term perception refers to the means by which information acquired from the environment via the sense organs is transformed into experiences of objects, events, sounds, tastes, etc. In this paper, we shall focus on the problem of object perception dealing exclusively with the visual modality. More precisely we will present a system, SVL - Symbolic Vision Lab, which is a development environment for object perception algorithms. SVL is mainly devoted to symbolic computation and can exploit for low level tasks a massively parallel computer, such as the general purpose Connection Machine, or an ad hoc specific VLSI architectures whose efficiency can be simulated in advance on the Connection Machine itself.

High-level and low-level computer vision: Towards an integrated approach / Adorni, G.; Broggi, A.; Conte, G.; D'Andrea, V.; Sansoe', C.. - STAMPA. - 549:(1991), pp. 322-331. (Intervento presentato al convegno 2nd Congress of the Italian Association for Artificial Intelligence, AI*IA 1991 tenutosi a Palermo, Italy nel October 1991) [10.1007/3-540-54712-6_244].

High-level and low-level computer vision: Towards an integrated approach

Conte G.;Sansoe' C.
1991

Abstract

The term perception refers to the means by which information acquired from the environment via the sense organs is transformed into experiences of objects, events, sounds, tastes, etc. In this paper, we shall focus on the problem of object perception dealing exclusively with the visual modality. More precisely we will present a system, SVL - Symbolic Vision Lab, which is a development environment for object perception algorithms. SVL is mainly devoted to symbolic computation and can exploit for low level tasks a massively parallel computer, such as the general purpose Connection Machine, or an ad hoc specific VLSI architectures whose efficiency can be simulated in advance on the Connection Machine itself.
1991
978-3-540-54712-9
978-3-540-46443-3
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2980224