Image Recognition in Digital Merchandising Industry

•

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IT Weekend

by Vitalii Yuryev

Technology Business

Image Recognition
in Digital Merchandising Industry

Digital Merchandising Benefits
• Improved Service Level Monitoring
• Reduced Data Collection Time
• Out of Stock Reduction
• Increase in SKU Availability
• Merchandiser Self-discipline

What is Computer Vision?
“Computer vision is a field that includes
methods for acquiring, processing,
analyzing, and understanding images in
order to produce numerical or symbolic
information”
Wikipedia

Computer Vision Evolution
Computer
Vision
Artificial
Intelligence
Image
Processing
Pattern
Recognition
Robotics
Machine Vision
1960s
1970s
Edge
detection
Line Labeling
1980s
1990s Face tracking
Face
recognition
2000s
Feature-based
recognition
Image-based
modeling
Image-based
rendering
Region-based
recognition
High dynamic
range
Emotion
recognition
Robotic
Vision
Neural network
based recognition
2010s
Physics
First digital
camera
Megapixel
sensor
CMOS chip
SURF
SIFT
ORB
BRIEF
FREAK
HOG GLOH
Haar-cascades
Viola-Jones
FAST
Latent SVM
Deep NN
LSTM NN
MD LSTM NN
RPROP
FR NN
BoW

Computer Vision Algorithms
• SURF
• SIFT
• FAST
• FREAK
• ORB
• RANSAC

Computer Vision Libraries
• OpenCV
• EmguCV
• FastCV
• JavaCV

0
10
20
30
40
50
60
70
80
90
0.3 0.6 0.7 0.8 0.9 1 1.2 2 3 5 8
Recognitionquality
Image size
Recognition quality depending on image size

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Image Recognition in Digital Merchandising Industry

1. Image Recognition in Digital Merchandising Industry

2. What is Merchandising?

3. Digital Merchandising Benefits • Improved Service Level Monitoring • Reduced Data Collection Time • Out of Stock Reduction • Increase in SKU Availability • Merchandiser Self-discipline

4. What is Computer Vision? “Computer vision is a field that includes methods for acquiring, processing, analyzing, and understanding images in order to produce numerical or symbolic information” Wikipedia

5. Computer Vision Evolution Computer Vision Artificial Intelligence Image Processing Pattern Recognition Robotics Machine Vision 1960s 1970s Edge detection Line Labeling 1980s 1990s Face tracking Face recognition 2000s Feature-based recognition Image-based modeling Image-based rendering Region-based recognition High dynamic range Emotion recognition Robotic Vision Neural network based recognition 2010s Physics First digital camera Megapixel sensor CMOS chip SURF SIFT ORB BRIEF FREAK HOG GLOH Haar-cascades Viola-Jones FAST Latent SVM Deep NN LSTM NN MD LSTM NN RPROP FR NN BoW

6. Recognition Steps

7. Image acquisition

8. Image preprocessing

9. Feature extraction

10. Descriptor extraction

11. Descriptor matching

12. Filtering

13. Object Identification

14. Demo

15. Algorithms and Libraries

16. Computer Vision Algorithms • SURF • SIFT • FAST • FREAK • ORB • RANSAC

17. Computer Vision Libraries • OpenCV • EmguCV • FastCV • JavaCV