Sensors 2011, 11(8), 8164-8179; doi:10.3390/s110808164
Article

FPGA-Based Multimodal Embedded Sensor System Integrating Low- and Mid-Level Vision

1 Department of Computer Architectures and Automatic Control, Complutense University of Madrid, 28040 Madrid, Spain 2 Department of Electrical and Computer Engineering, FAMU-FSU College of Engineering, Tallahassee, FL 32310, USA
* Author to whom correspondence should be addressed.
Received: 16 February 2011; in revised form: 6 July 2011 / Accepted: 15 August 2011 / Published: 22 August 2011
(This article belongs to the Special Issue Bioinspired Sensor Systems)
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Abstract: Motion estimation is a low-level vision task that is especially relevant due to its wide range of applications in the real world. Many of the best motion estimation algorithms include some of the features that are found in mammalians, which would demand huge computational resources and therefore are not usually available in real-time. In this paper we present a novel bioinspired sensor based on the synergy between optical flow and orthogonal variant moments. The bioinspired sensor has been designed for Very Large Scale Integration (VLSI) using properties of the mammalian cortical motion pathway. This sensor combines low-level primitives (optical flow and image moments) in order to produce a mid-level vision abstraction layer. The results are described trough experiments showing the validity of the proposed system and an analysis of the computational resources and performance of the applied algorithms.
Keywords: bio-inspired systems; machine vision; optical flow; orthogonal variant moments; VLSI

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MDPI and ACS Style

Botella, G.; Martín H., J.A.; Santos, M.; Meyer-Baese, U. FPGA-Based Multimodal Embedded Sensor System Integrating Low- and Mid-Level Vision. Sensors 2011, 11, 8164-8179.

AMA Style

Botella G, Martín H. JA, Santos M, Meyer-Baese U. FPGA-Based Multimodal Embedded Sensor System Integrating Low- and Mid-Level Vision. Sensors. 2011; 11(8):8164-8179.

Chicago/Turabian Style

Botella, Guillermo; Martín H., José Antonio; Santos, Matilde; Meyer-Baese, Uwe. 2011. "FPGA-Based Multimodal Embedded Sensor System Integrating Low- and Mid-Level Vision." Sensors 11, no. 8: 8164-8179.

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