Abstract
In this chapter, we propose a design and verification environment for computational demanding and secure embedded vision-based systems. Starting with an executable specification in OpenCV, we provide subsequent refinements and verification down to a system-on-chip prototype into an FPGA-based smart camera. At each level of abstraction, properties of image processing applications are used along with structure composition to provide a generic architecture that can be automatically verified and mapped to a lower abstraction level, the last of which being the FPGA. The result of this design flow is a framework that encapsulates the computer vision library OpenCV at the highest level, integrates Accelera’s SystemC/TLM with the Universal Verification Methodology (UVM) and QEMU-OS for virtual prototyping, verification, and low-level mapping.
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Assertion-Based Verification. Springer, US. doi:
Axi interconnect. http://www.xilinx.com/products/intellectual-property/axi_interconnect.htm
Generic and automatic specman based verification environment for image signal processing ips. http://design-reuse.com/articles/20907/specman-verification-image-signal-processing-ip
Aghajan H, Cavallaro A (2009) Multi-camera networks: principles and applications. Academic Press, Waltham
Alfaro L, Henzinger T, Interface-based design 195:83–104. doi:10.1007/1-4020-3532-23
Appiah K, Hunter A, Kluge T, Aiken P, Dickinson P (2009) FPGA-based anomalous trajectory detection using SOFM. In: Proceedings of the 5th international workshop on reconfigurable computing: architectures, tools and applications, ARC’09, pp 243–254. Springer, Berlin. doi:10.1007/978-3-642-00641-8_24
Bramberger M, Doblander A, Maier A, Rinner B, Schwabach H (2006) Distributed embedded smart cameras for surveillance applications. IEEE Comput Soc 39:68–75
Chen P, Ahammad P, Boyer C, Huang SI, Lin L, Lobaton E, Meingast M, Oh S, Wang S, Yan P, Yang AY, Yeo C, Chang LC, Tygar D, Sastry SS (2008) Citric: a low-bandwidth wireless camera network platform. In: Second ACM/IEEE international conference on distributed smart cameras, pp 1–10
Guenard N, Hamel T, Mahony R (2008) A practical visual servo control for an unmanned aerial vehicle. IEEE Trans Rob 24(2):331–340. doi:10.1109/TRO.2008.916666
Kim J, Sukkarieh S (2004) Slam aided GPS/INS navigation in GPS denied and unknown environments. In: The 2004 international symposium on GNSS/GPS, Sydney, pp 6–8
Kim K, Chalidabhongse TH, Harwood D, Davis L (2005) Real-time foreground-background segmentation using codebook model. Real-Time Imaging 11(3):172–185. doi:10.1016/j.rti.2004.12.004
Lin F, Lum KY, Chen B, Lee T, Development of a vision-based ground target detection and tracking system for a small unmanned helicopter. Sci China Ser F. Inf Sci 52(11):2201–2215. doi:10.1007/s11432-009-0187-5
Mefenza M, Yonga F, Bobda C (2013) Razorcam: an embedded platform for image processing. In: ASEE midwest conference
Mefenza M, Yonga F, Bobda C (2013) ACM hotmobile 2013 poster: Razorcam: a prototyping environment for video communication. SIGMOBILE Mob Comput Commun Rev 17(3):13–14. doi:10.1145/2542095.2542103
Meingast M, Geyer C, Sastry S (2004) Vision based terrain recovery for landing unmanned aerial vehicles. In: 43rd IEEE conference on decision and control (CDC), 2004, vol. 2, pp 1670–1675. doi:10.1109/CDC.2004.1430284.
Nieto M, Cuevas C, Salgado L, Garcia N (2011) Line segment detection using weighted mean shift procedures on a 2d slice sampling strategy. Pattern Anal Appl 14(2):149–163. doi:10.1007/s10044-011-0211-4
Park J, Lee B, Lim K, Kim J, Kim S, Kwang-Hyun-Baek (2008) Co-simulation of SystemC TLM with RTL HDL for surveillance camera system verification. In: 15th IEEE international conference on electronics, circuits and systems, 2008 (ICECS 2008), pp 474–477. doi:10.1109/ICECS.2008.4674893
Rinner B, Winkler T, Schriebl W, Quaritsch M, Wolf W (2008) The evolution from single to pervasive smart cameras. In: Second ACM/IEEE international conference on distributed smart cameras, 2008 (ICDSC 2008), pp 1–10. doi:10.1109/ICDSC.2008.4635674
Rose A, Swan S, Pierce J, Fernandez J (2005) Transaction level modeling in SystemC. Open SystemC Initiative 1(1.297)
Saha S (2007) Design methodology for embedded computer vision systems. PhD thesis
Samsom H, Franssen F, Catthoor F, De Man H (1995) System level verification of video and image processing specifications. In: Proceedings of the 8th international symposium on system synthesis, 1995, pp 144–149. doi:10.1109/ISSS.1995.520626
Schlessman J, Chen CY, Wolf W, Ozer B, Fujino K, Itoh K (2006) Hardware/software co-design of an fpga-based embedded tracking system. In: Conference on computer vision and pattern recognition workshop, 2006 (CVPRW’06), pp 123–123. doi:10.1109/CVPRW.2006.92
Trost A, Zemva A (2012) Verification structures for design of video processing circuits. In: MIPRO, 2012 proceedings of the 35th international convention, pp 222–227
Wu S, Implementing an automated checking scheme for a video-processing device. www.cadence.com/rl/Resources/conference_papers/1.13Paper
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Mefenza, M., Yonga, F., Bobda, C. (2014). Design and Verification Environment for High-Performance Video-Based Embedded Systems. In: Bobda, C., Velipasalar, S. (eds) Distributed Embedded Smart Cameras. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7705-1_4
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DOI: https://doi.org/10.1007/978-1-4614-7705-1_4
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