On the Design of Change-driven Data-flow Algorithms and Architectures for High-speed Motion Analysis

Jose A. Boluda, Pedro Zuccarello, Fernando Pardo, Francisco Vegara

Abstract

Motion analysis is a computationally demanding task due to the large amount of data involved as well as the complexity of the implicated algorithms. In this position paper we present some ideas about data-flow architectures for processing visual information. Selective Change Driven (SCD) is based on a CMOS sensor which delivers, ordered by the absolute magnitude of its change, only the pixels that have changed after the last time they were read-out. As a natural step, a processing architecture based on processing pixels in a data-flow method, instead of processing complete frames, is presented. A data-flow FPGA-based architecture is appointed in developing such concepts.

References

  1. Boluda, J., Zuccarello, P., Pardo, F., and Vegara, F. (2011). Selective Change Driven Imaging: A Biomimetic Visual Sending Strategy. Sensors, 11(11):1100-11020.
  2. Camunas-Mesa, L., Perez-Carrasco, J., Zamarreno-Ramos, C., Serrano-Gotarredona, T., and Linares-Barranco, B. (2010). On Scalable Spiking ConvNet Hardware for Cortex-Like Visual Sensory Processing System. In Proc. of the 2010 IEEE International Symposium on Circuits and Systems, pages 249-252, Paris, France. .
  3. Chi, Y., Mallik, U., Clapp, E., Choi, E., Cauwenberghs, G., and Etienne-Cummings, R. (2007). CMOS camera with in-pixel temporal change detection and ADC. IEEE Journal of Solid-State Circuits, 42(10):2187- 2196.
  4. Gollisch, T. and Meister, M. (2010). Eye smarter than scientist believed: Neural computations in circuits of the Retina. Neuron, 65():150-164.
  5. Higgins, C. and Koch, C. (2000). A Modular Multi-Chip Neuromorphic Architecture for Real-Time Visual Motion Processing. Analog Integrated Circuits and Signal Processing, 24(3):195-211.
  6. Lichtsteiner, P., Posch, C., and Delbrück, T. (2008). A 128x128 dB 15 µs latency asynchronous temporal contrast vision sensor,. IEEE Journal of Solid-State Circuits, 43(2):566-576.
  7. Mahowald, M. (1992). VLSI Analogs of neural visual processing: A synthesis of form and function. PhD thesis, Computer Science Divivision, California Institute of Technology, Pasadena, CA.
  8. Pardo, F., Zuccarello, P., Boluda, J., and Vegara, F. (2011). Advantages of Selective Change Driven Vision for resource-limited systems. IEEE Transactions on Circuits and Systems for Video Technology, 21(10):1415- 1423.
  9. Zuccarello, P., Pardo, F., de la Plaza, A., and Boluda, J. (2010). 32x32 winner-take-all matrix with single winner selection. Electronics Letters, 46(5):333-335.
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Paper Citation


in Harvard Style

Boluda J., Zuccarello P., Pardo F. and Vegara F. (2012). On the Design of Change-driven Data-flow Algorithms and Architectures for High-speed Motion Analysis . In Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-8565-21-1, pages 548-553. DOI: 10.5220/0004120805480553


in Bibtex Style

@conference{icinco12,
author={Jose A. Boluda and Pedro Zuccarello and Fernando Pardo and Francisco Vegara},
title={On the Design of Change-driven Data-flow Algorithms and Architectures for High-speed Motion Analysis},
booktitle={Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2012},
pages={548-553},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004120805480553},
isbn={978-989-8565-21-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - On the Design of Change-driven Data-flow Algorithms and Architectures for High-speed Motion Analysis
SN - 978-989-8565-21-1
AU - Boluda J.
AU - Zuccarello P.
AU - Pardo F.
AU - Vegara F.
PY - 2012
SP - 548
EP - 553
DO - 10.5220/0004120805480553