Seal of Good Local Governance (SGLG) 2024Final.pptx
Stereo matching for 2d face recognition
1. DESIGN AND DEVELOPMENT FOR FACE
RECOGNITION USING STEREO MATCHING
ALGORITHM
by
N.M.Harish Balaji
Sankara College of Science and Commerce
2. INTRODUCTION
• Face Recognition(FR) - images & videos.
• Face recognition compliments face detection .
• Face detection - finds faces in images and videos .
• Problems in FR - to handle pose variation .
• 2 predominant methods
1) Geometric approach
2) Photometric approach
3. SECTIONS IN FACE RECOGNITION
Face Recognition deals with 3 main sections, they are:
1. Images with 3 landmarks in face.
2. Illumination variation.
3. Pose variation.
4. BRIEF PROCESS
• FR handles pose & illumination variations.
• Gallery image is generated with 4 landmark points.
• Similarities are identified using matching cost.
• Works well for large pose variations.
• Dramatic changes is a challenging problem that an face
recognition system needs to face.
5. FEATURES
• Feature based system - detects - facial landmarks.
• Initially face images need to be aligned.
1. To generate landmark points - Eyes, Nose, Mouth.
2. Fourth landmark - stereo.
• Stereo - 3*3 filter - calculates the distance between
test image & training image.
6. FACE RECOGNITION METHOD
• Stereo Matching - supports good correspondence.
• Dynamic programming - 2D face images.
• Stereo algorithm - maximizes the cost function.
15. CONCLUSION
• Simple general method - reduces illumination changes.
• Performance is good - accurate as well.
• ADVANTAGE : Automatic face recognition system.