Vol. 48 No. SIG 1(CVIM 17) Feb Visconti Visconti ITS Image Recognition LSI Visconti and Its Applications to Safety and Security Hiroaki Nakai, J
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1 Vol. 48 No. SIG 1(CVIM 17) Feb Visconti Visconti ITS Image Recognition LSI Visconti and Its Applications to Safety and Security Hiroaki Nakai, Jun Tanabe, Kenji Furukawa, Tatsuo Kozakaya, Takashi Miyamori, Yasuhiro Taniguti, Yukimasa Miyamoto and Ken-ichi Maeda In this paper, we present several examples of practical developments in image recognition technologies for use in automotive and security applications. The first example is image processing hardware; where Visconti is perhaps the most efficient platform for visual sensing techniques. The second comprises various image processing algorithms for the sensing of surrounding obstacles to automobiles, human faces and conditions. Combination of such hardware and software form a smart sensor; which are widely expected to become pervasive in many aspects of daily life. 1. CCD CMOS 1) Corporate Research & Development Center, Toshiba Corporation Center for Semiconductor Research & Development, Semiconductor Company, Toshiba Corporation ITS
2 2 Feb LSI ECU Electronic Control Unit 100 ECU 1 2),3) ECU 1 ECU ECU LSI LSI 1 LSI LSI LSI 1) 2) 3) 3 4) 1) LSI 5) LSI LSI 2) LSI FPGA Field Programmable Gate Array 6),7) LSI ECU 7) 3) CPU DSP CPU SuperVchip 9) EyeQ 10) Intel MMX/SSE Motorola AltiVec DSP Visconti 3 DSP
3 Vol. 48 No. SIG 1(CVIM 17) Visconti 3 1 Visconti Fig. 1 Micrograph and block diagram of Visconti. Vision Instruction Processor 11) IMAP-CE 12) 12) 2.2 Visconti Visconti 1 13),14) i) ii) iii) Visconti MeP Media embedded Processor 15),16) MeP LSI 17) Visconti CPU 18),19) ) 8) MeP 17) Visconti SIMD Single Instruction Multiple Data SIMD 2 RISC Reduced Instruction Set Computer 1 3 VLIW Very Long Instruction Word MeP 15) VLIW 13) MeP 3 VLIW SIMD 3 MeP DMA Visconti MeP 3 3-way VLIW ) 4-way VLIW SIMD 12) 1.66
4 4 Feb Visconti Table 1 Specifications of Visconti. Feature Specification Technology 0.13 µm CMOS6-layermetal Peak performance 18 GOPS (6 GOPS 3 processors) Clock frequency 150 MHz No. of transistors 21 million (17 million for memory) On-chip memory 260 Kbytes Power consumption 1.5V Chip size 6.98 mm 6.98 mm (48.7 mm 2 ) Package 456 pin PBGA double buffering 3.2 MeP 16) Visconti MHz 18 GOPS 3 1W 40 C +85 C Visconti 3 VGA 1 2 Visconti 3. 2 Fig. 2 Prototype processing hardware. 4 Visconti ) 22) a b a b 1 4 5
5 Vol. 48 No. SIG 1(CVIM 17) Visconti 5 Fig. 3 3 Surveillance system for automobiles. 4 Fig. 4 A preceding vehicle detection based on motion of horizontal segments. 5 4 A B C D Fig. 5 Four colinear points and four coplanar parallel horizontal segments on the surface plane of an obstacle. 4 I ABCD = AC BD = δ ac δbd AD DC δ ad δ dc IJ δ ij I J i j y = y =0 l d 3 y a (t 2 ) y c (t 2 ) y a (t 1 ) y c (t 1 ) = y b(t 2 ) y c (t 2 ) y b (t 1 ) y c (t 1 ) = M v y a (t 2 ) 1 y c (t 2 ) 1 y a (t 1 ) 1 y c (t 1 ) = y b(t 2 ) 1 y c (t 2 ) 1 1 y b (t 1 ) 1 y c (t 1 ) 1 = M h y i (t) t i y 3 y 21) 1) 2) 3) 4) Visconti 1) x y 2) 3) 23) Orientation Code 24) SIMD double buffering 4) 2) 3) Visconti
6 6 Feb frame Table 2 Effect of optimized implementation on execution time. [µs] [µs] 10,162 3,884 74,849 2, ,369 2,793 7,694 1, ,058 14,956 Fig. 7 7 Image regions for boundary determination. 8 6 Fig. 8 Examples of detection results under severe imaging conditions (rain, night). Fig. 6 Schematic view of planar-projective stereo method. d) ) 26) 6 a) b) c) 27) 7 7 R-R Q-Q 3 8 Visconti SIMD 30 28) integral image
7 Vol. 48 No. SIG 1(CVIM 17) Visconti 7 29) 30) Visconti Visconti 3.3 CPU 31) Visconti 32) ) CMSM: Constrained Mutual Subspace Method 34),35) CMSM MSM: Mutual Subspace Method 11 1 Conventional MSM 10 Fig. 10 Circular separability filter and detected candidates for feature points. Conventional MSM Fig. 9 9 Face identification system. 11 Fig. 11 Schematic view of Mutual Subspace Method.
8 8 Feb Fig. 12 Conceptual diagram of Constrained Mutual Subspace Method. 13 Fig. 13 Dynamic task assignment to three MeP modules. CMSM 2 P Q P C Q C 12 2 θ cos 2 θ = sup u C 0, v C 0 (u C, v C ) u C 2 v C 2 u C v C u C P C v C Q C Visconti 3 32) Visconti ) S/N 1) ROI 14 2) ROI 3) 3 ROI 14 D(t) D(t) R(t) 14 R(t) R T S/N ROI
9 Vol. 48 No. SIG 1(CVIM 17) Visconti 9 15 Fig. 15 Examples of respiration measurement results (upper: a healthy person, lower: a patient of Sleep Apnea Syndrome). 14 ROI Fig. 14 Examples of ROI-setting result and respiration signal. 4. ROI 15 37) 38) Visconti MeP 1 30 Visconti MeP LSI Visconti 1) Vol.59, No.5, pp (2005). 2) Vol.59, No.5, pp.4 9 (2005). 3) Scharnhorst, T.: Management of the E/E Complexity by Introducing a Software DevelopmentProcessandtheOpenSystemArchitecture, 6th Braunschweig Conference on Automation, Assistance and Embedded Real Time Platforms for Transportation, AAET, Vol.1,
10 10 Feb pp (2005). 4) Dasu, A., et al.: A Survey of Media Processing Approaches, IEEE Trans. Circuits and Systems for Video Technology, Vol.12, No.8, pp (2002). 5) Hanawa, K., et al.: Development of Stereo Image Recognition System for ADA, IEEE Intelligent Vehicles Symposium, pp (2001). 6) Tessier, R., et al.: Reconfigurable Computing for Digital Signal Processing: A Survey, Journal of VLSI Signal Processing, Vol.28, No.1, pp.7 27 (2000). 7) Todman, T.J., et al.: Reconfigurable computing: Architectures and design methods, IEE Proc.Computers & Digital Techniques, Vol.152, No.2, pp (2005). 8) Kisacanin, B.: Examples of Low-Level Computer Vision on Media Processors, The 1st IEEE Workshop on Embedded Computer Vision (2005). 9) LSI SuperVchip 7 pp.5 10 (2001). 10) Stein, G.P., et al.: A Computer Vision System on a Chip: A case study from the automotive domain, The 1st IEEE Workshop on Embedded Computer Vision (2005). 11) Raab, W., et al.: A 100-GOPS Programmable Processor for Vehicle Vision Systems, IEEE Design & Test of Computers, pp.8 15 (2003). 12) Kyo, S., et al.: An Integrated Memory Array Processor Architecture for Embedded Image Recognition Systems, 32nd Intr. Symposium on Computer Architecture, ISCA 05, pp (2005). 13) Tanabe, J., et al.: Visconti: Multi-VLIW Image Recognition Processor based on Configurable Processor, IEEE Custom Integrated Circuits Conference, CICC, pp (2003). 14) Miyamori, T., et al.: Development of Image Recognition Processor Based on Configurable Processor, Journal of Robotics and Mechatronics, Vol.17, No.4, pp (2005). 15) Media embedded Processor. 16) Miyamori, T.: A Configurable and Extensible Media Processor, Embedded Processor Forum (2002). 17) MeP SoC Vol.58, No.5, pp.9 13 (2003). 18) Kondo, Y., et al.: A 4GOPS 3Way-VLIW Image Recognition Processor Based on a Configurable Media-processor, International Solid- State Circuits Conference, ISSCC, digest of technical papers, pp (2001). 19) Takano, H., et al.: A 4GOPS 3 Way-VLIW Image Recognition Processor Based on a Configurable Media Processor, IEICE Trans. ELEC- TRON, Vol.E85-C, No.2, pp (2002). 20) Taniguchi, Y., et al.: Automatic Rear and Side Surveillance System Using Image Processing, 6th World Congress on ITS, Paper No.3026 (1999). 21) LSI 9 pp (2003). 22) D-II Vol.J87-D-II, No.12, pp (2004). 23) Fukui, K.: Edge Extraction Method based on Separability of Image Features, IEICE Trans. Inf. & Syst., Vol.E-78-D, No.12, pp (1995). 24) Ullah, F., et al.: Orientation Code Matching For Robust Object Search, IEICE Trans. Inf. &Syst., Vol.E84-D, No.8, pp (2001). 25) Nakai, H., et al.: A Practical Stereo Scheme for Obstacle Detection in Automotive Use, International Conference on Pattern Recognition, ICPR, Vol.3, pp (2004). 26) CVIM-93-7, pp (1995). 27) Hattori, H., et al.: Stereo without Depth Search and Metric Calibration, IEEE Conference on Computer Vision and Pattern Recognition, CVPR, Vol.1, pp (2000). 28) Vol.89, No.3, pp (2005). 29) Hattori, H., et al.: Dense stereo matching in restricted disparity space, IEEE Intelligent Vehicles Symposium, pp (2005). 30) 8 pp (2002). 31) FacePass 32) Visconti 10 pp (2004). 33) D-II Vol.J80-D-II, No.8, pp (1997). 34) D-II Vol.J82-D-II, No.4, pp (1999). 35)
11 Vol. 48 No. SIG 1(CVIM 17) Visconti 11 Vol.45, No.3, pp (2004). 36) D-II Vol.J83-D-II, No.1, pp.1 9 (1999). 37) Vol.16, No.2, pp (1998). 38) ( ) ( ) ITS SoC IEEE SoC 1976 IEEE Senior Member
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