Advantages of selective change-driven vision for resource-limited systems

IEEE Transactions on Circuits and Systems for Video Technology

Volumn 21, Issue 10, 2011, Pages 1415-1423

  Pardo, Fernando ^a   Zuccarello, Pedro ^a   Boluda, Jose A ^a   Vegara, Francisco ^a  

^a UNIVERSITY OF VALENCIA   (Spain)

Author keywords

Real time image processing; resource limited systems; selective change driven (SCD) vision

Indexed keywords

CMOS SENSORS; DIRECT IMPACT; IMAGE FLOWS; OBJECT TRACKING; PIXEL FLOW; PROCESSING HARDWARE; REAL TIME CONSTRAINTS; REAL-TIME IMAGE PROCESSING; VISION APPLICATIONS; VISION PROCESSING; VISION SYSTEMS; VISUAL INFORMATION;

CMOS INTEGRATED CIRCUITS; EXPERIMENTS; IMAGE PROCESSING; PIXELS;

REAL TIME SYSTEMS;

EID: 80053462429     PISSN: 10518215     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCSVT.2011.2162761     Document Type: Article

References (23)

1. T. Gollisch and M. Meister, "Eye smarter than scientists believed: Neural computations in circuits of the retina," Neuron, vol. 65, no. 2, pp. 150-164, Jan. 2010.
2. F. Pardo, J. A. Boluda, F. Vegara, and P. Zuccarello, "On the advantages of asynchronous pixel reading and processing for high-speed motion estimation," in Proc. ISVC, Dec. 2008, pp. 205-215.
3. J. A. Boluda, F. Vegara, F. Pardo, and P. Zuccarello, "Selective changedriven image processing: A speeding-up strategy," in Proc. CIARP, Nov. 2009, pp. 37-44.
4. F. Vegara, J. A. Boluda, J. Domingo, F. Pardo, and X. Benavent, "Accelerating motion analysis algorithms with a pixel change-driven scheme," in Proc. Int. Conf. IPCV, Jul. 2009, pp. 895-900.
5. J. C. Sosa, J. A. Boluda, F. Pardo, and R. Ǵomez-Fabela, "Changedriven data flow image processing architecture for optical flow computation," J. Real-Time Image Process., vol. 2, no. 4, pp. 259-270, Dec. 2007. (Pubitemid 350241111)
6. M. A. Mahowald, "VLSI analogs of neural visual processing: A synthesis of form and function," Ph.D. dissertation, Dept. Computat. Neural Syst., California Inst. Technol., Pasadena, May 1992.
7. P.-F. R̈uedi, P. Heim, F. Kaess, E. Grenet, F. Heitger, P.-Y. Burgi, S. Gyger, and P. Nussbaum, "A 128x128 pixel 120-dB dynamicrange vision-sensor chip for image contrast and orientation extraction," IEEE J. Solid-State Circuits, vol. 38, no. 12, pp. 2325-2333, Sep. 2003.
8. S. Kameda and T. Yagi, "A silicon retina system that calculates direction of motion," in Proc. ISCAS, vol. 4. 2003, pp. 792-795.
9. K. Aizawa, Y. Egi, T. Hamamoto, M. Hatori, M. Abe, H. Maruyama, and H. Otake, "Computational image sensor for on sensor compression," IEEE Trans. Electron Devices, vol. 44, no. 10, pp. 1724-1730, Oct. 1997. (Pubitemid 127764709)
10. T. Hamamoto, R. Ooi, Y. Ohtsuka, and K. Aizawa, "Real-time image processing by using image compression sensor," in Proc. ICIP, vol. 3. Oct. 1999, pp. 935-939. (Pubitemid 30550184)
11. K. Boahen, "The retinomorphic approach: Pixel-parallel adaptive amplification, filtering, and quatization," Analog Integr. Circuits Signal Process., vol. 13, no. 1-2, pp. 53-68, May 1997. (Pubitemid 127507961)
12. C. M. Higgins and C. Koch, "A modular multi-chip neuromorphic architecture for real-time visual motion processing," Analog Integr. Circuits Signal Process., vol. 24, no. 3, pp. 195-211, 2000.
13. J. Kramer, "An on/off transient imager with event-driven, asynchronous read-out," in Proc. ISCAS, 2002, pp. 165-168.
14. P. Lichtsteiner, C. Posch, and T. Delbr̈uck, "A 128x128 dB 15 μs latency asynchronous temporal contrast vision sensor," IEEE J. Solid-State Circuits, vol. 43, no. 2, pp. 566-576, Feb. 2008. (Pubitemid 351190224)
15. M. Gottardi, N. Massari, and S. A. Jawed, "A 100 μW 128x64 pixels contrast-based asyncrhonous binary vision sensor for sensor networks applications," IEEE J. Solid State Circuits, vol. 44, no. 5, pp. 1582-1592, May 2009.
16. Y. M. Chi, U. Mallik, M. A. Clapp, E. Choi, G. Cauwenberghs, and R. Etienne-Cummings, "CMOS camera with in-pixel temporal change detection and ADC," IEEE J. Solid-State Circuits, vol. 42, no. 10, pp. 2187-2196, Oct. 2007. (Pubitemid 47483001)
17. E. Ö zalevli and C. M. Higgins, "Reconfigurable biologically inspired visual motion systems using modular neuromorphic VLSI chips," IEEE Trans. Circuits Syst., vol. 52, no. 1, pp. 79-92, Jan. 2005.
18. K. A. Zaghlioul and K. Hoahen, "Optic nerve signals in a neuromorphic chip II: Testing and results," IEEE Trans. Biomed. Eng., vol. 51, no. 4, pp. 667-675, Apr. 2004.
19. E. Culurciello and R. Etienne-Cummings, "A biomorphic digital image sensor," IEEE J. Solid State Circuits, vol. 38, no. 2, pp. 281-294, Feb. 2003.
20. R. Serrano-Gotarredona, M. Oster, P. Lichtsteiner, A. Linares-Barranco, R. Paz-Vicente, F. Ǵomez-Rodŕiguez, L. Camunas-Mesa, R. Berner, M. Rivas-Ṕerez, T. Delbruck, S.-C. Liu, R. Douglas, P. Hafliger, G. Jiḿenez-Moreno, A. C. Ballcels, T. Serrano-Gotarredona, A. J. Acosta-Jiḿenez, and B. Linares-Barranco, "CAVIAR: A 45k neuron, 5M synapse, 12G connects/s AER hardware sensory-processing-learningactuating system for high-speed visual object recognition and tracking," IEEE Trans. Neural Netw., vol. 20, no. 9, pp. 1417-1438, Sep. 2009.
21. C. Posch, D. Matolin, and R. Wohlgenannt, "High-DR frame-free PWM imaging with asynchronous AER intensity encoding and focal-plane temporal redundancy supression," in Proc. IEEE ISCAS. May 2010, pp. 2430-2433.
22. A. Moini, Vision Chips. Norwell, MA: Kluwer, 2000.
23. P. Zuccarello, F. Pardo, A. de la Plaza, and J. A. Boluda, "32x32 winnertake-all matrix with single winner selection," Electron. Lett., vol. 46, no. 5, pp. 333-335, Mar. 2010.