1 Welcome to computer vision

This chapter covers

  • Components of the vision system
  • Applications of computer vision
  • Understanding the computer vision pipeline
  • Preprocessing images and extracting features
  • Using classifier learning algorithms

Hello! I’m very excited that you are here. You are making a great decision--to grasp deep learning (DL) and computer vision (CV). The timing couldn’t be more perfect. CV is an area that’s been advancing rapidly, thanks to the huge AI and DL advances of recent years. Neural networks are now allowing self-driving cars to figure out where other cars and pedestrians are and navigate around them. We are using CV applications in our daily lives more and more with all the smart devices in our homes--from security cameras to door locks. CV is also making face recognition work better than ever: smartphones can recognize faces for unlocking, and smart locks can unlock doors. I wouldn’t be surprised if sometime in the near future, your couch or television is able to recognize specific people in your house and react according to their personal preferences. It’s not just about recognizing objects--DL has given computers the power to imagine and create new things like artwork; new objects; and even unique, realistic human faces.

1.1 Computer vision

1.1.1 What is visual perception?

1.1.2 Vision systems

1.1.3 Sensing devices

1.1.4 Interpreting devices

1.2 Applications of computer vision

1.2.1 Image classification

1.2.2 Object detection and localization

1.2.3 Generating art (style transfer)

1.2.4 Creating images

1.2.5 Face recognition

1.2.6 Image recommendation system

1.3 Computer vision pipeline: The big picture

1.4 Image input

1.4.1 Image as functions

1.4.2 How computers see images

1.4.3 Color images

1.5 Image preprocessing

1.5.1 Converting color images to grayscale to reduce computation complexity

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