What is Computer Vision?
Computer vision is the field of AI that enables computers to interpret and understand visual information from images and videos. It's how your phone recognizes faces, cars detect pedestrians, and doctors spot tumors in scans.
Fun Fact
To a computer, an image is just a grid of numbers (pixel values). Computer vision is the art of extracting meaning from those numbers.
Key Computer Vision Tasks
Image Classification
Identifying what's in an image. "This photo contains a cat." Used in photo organization, content moderation, medical diagnosis.
Object Detection
Finding and locating multiple objects. "There's a cat at position (x,y) and a dog at position (a,b)." Essential for self-driving cars, security cameras.
Image Segmentation
Identifying exactly which pixels belong to each object. Used in medical imaging, photo editing, autonomous driving.
Facial Recognition
Identifying specific faces. Powers phone unlock, photo tagging, security systems.
Pose Estimation
Detecting human body positions. Used in fitness apps, motion capture, sports analysis.
How It Works
Convolutional Neural Networks (CNNs)
The breakthrough technology for computer vision. CNNs use "filters" that slide across images, detecting features like edges, textures, and shapes at different levels of abstraction.
The Hierarchy of Features
- Early layers — Detect edges and simple patterns
- Middle layers — Detect shapes and textures (eyes, fur)
- Deep layers — Detect complex objects (faces, cars)
Real-World Applications
- Autonomous vehicles — Detecting pedestrians, signs, lanes
- Medical imaging — Finding tumors, analyzing X-rays
- Retail — Checkout-free stores, inventory management
- Manufacturing — Quality control, defect detection
- Agriculture — Crop monitoring, pest detection
- Security — Video surveillance, access control
Challenges
- Lighting variations — Same object looks different in different light
- Occlusion — Objects partially hidden by others
- Viewpoint changes — Same object from different angles
- Adversarial attacks — Tricking AI with subtle modifications
- Bias — Models may perform worse on underrepresented groups
Summary
- • Computer vision enables AI to interpret visual information
- • Key tasks: classification, detection, segmentation, recognition
- • CNNs are the core technology behind modern computer vision
- • Applications range from self-driving cars to medical diagnosis