What is Computer Vision?

Humans use their vision to see things and then they interpret those via their brain. Similarly, computer vision is to make computers perceive, process and understand visual data such  as images and videos. The ultimate goal of computer vision is to model, replicate, and more importantly exceed human vision using computer software and hardware at different levels. It needs knowledge in computer science, electrical engineering, mathematics, physiology, biology, and cognitive science.

 

 

 

 

The Computer Vision Hierarchy:

• Low-level vision: Processing the image for extracting the features such as edges, corners.
• Middle-level vision: Object recognition, motion analysis, and 3-D reconstruction using the features obtained from low-level vision.
• High-level vision: Interpretation of the information from middle level. Interpretation may include a conceptual description of a scene like activity, intention, and behavior.

Computer vision is, in some ways, the inverse of computer graphics. While computer graphics produces image data from 3D models, computer vision often produces 3D models from image data. Computer vision includes 3D analysis from 2D images. This analyzes the 3D scene projected onto one or several images, e.g., how to reconstruct structure or other information about the 3D scene from one or several images. Computer vision often relies on more or less complex assumptions about the scene depicted in an image. (via  wiki)

Typical tasks of computer vision:

1. Recognition
2. Motion Analysis
3. Scene Construction
4. Image Restoration

The applications of computer vision are numerous and include:

• Augmented Reality
• Autonomous Vehicles
• Biometrics
• Character Recognition
• Forensics
• Face Recognition
• Gesture Analysis
• Medical Image Analysis
• Process Control
• Remote Sensing
• Robotics
• Security and Surveillance
• Transport