product wise computer vision development
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TRANSCRIPT
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Product-Wise Computer Vision Development
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Agenda
• Common CV Development Process
• Pitfalls
• Why this happens
• Suggested Computer Vision Process
• Future CV Development
• About me
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Common CV DevelopmentDevelop algorithm on Matlab
PC Demo PC Product
Port Algorithm to Platform1
Port Algorithm to Platform2
Initial Demo
Realtime Demo
PC Product
Mobile Product
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What’s wrong with it
• Matlab code is written as “demo”/PoC
• Fast, Dirty
• written with low development resource
• use proprietary algorithms
Develop algorithm on Matlab
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What’s wrong with it
• This step sometime includes:
• understanding mobile requirements
• Optimization to platform’s SIMD
• Memory optimization
• sometime full re-written of the algorithm since its too computationally intensive for mobile
Port Algorithm to Platform1
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Contributing factors to common CV Project Process • Matlab stage
• As a university or a garage SU, developers have low development resources
• PC Stage
• NIH - Developers prefer their proprietary version over popular algorithms.
• at this stage (PoC/Demo) developers doesn't think on mobile optimization
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Contributing factors to common CV Project Process
• Platform Stage
• Optimization starts from high memory and CP resource demanding PC code
• A considerable portion of the code doesn’t use standard OpenCV functions and requires hand made SIMD optimization
• Sometimes companies discover that the algorithm is too resource demanding and re-writes the algorithm for the mobile platform
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Product-wise Computer Vision Development
Develop initial PoC with OpenCV
PC Product RT Demo
Use platform-X optimized OpenCV for product (FastCV, TADP, CEVA-CV)
fixed-point ported non-OpenCV Algorithms Minimize Memory
requirements
Initial Demo
PC ProductPlatform agnostic
Optimized code
Platform Optimized
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Product-wise Computer Vision development
• Product wise CV development is guided by the vision of a multi-platform product. This leads to:
• Relay on a common CV library->OpenCV
• minimization of non-OpenCV functions (saves platform specific SIMD optimization)
• Separate between PC Product and optimized C code used as base for porting to mobile / embedded platforms
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Future Development with OpenVX
• Khronos compliant SoC will conform to a unified “OpenCV-Like” API
• Enables easy porting to all supporting platforms
•
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Yossi Cohen - About Me
• Android & Video Lecturer
• Video Architect & Developer
• Computer Vision Consultant
• Android Native Developer
Yossi Cohen
+972545313092