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1. How do we see and understand objects?
2. What does Computer Vision aim to achieve in training machines?
Before we go into the details of Computer Vision let us first play a game to understand it.
21 st Century #Creativity
Skills
GAME 01 Emoji Scavenger Hunt
Visit https://emojiscavengerhunt.withgoogle.com/ or scan the QR code to play
the game.
In this game, you will be tasked with finding 8 items within the time limit.
Answer the following questions, after playing the game:
1. Did you like the game?
2. Were you able to play successfully? If yes, how many attempts did it take?
3. Did you manage to win the game? If yes, what strategy or approach did you use to win?
4. Did the lighting in the room affect the machine's ability to identify items?
5. How many items did you show to the computer camera?
Computer Vision and Artificial Intelligence
Computer Vision is a part of Artificial Intelligence (AI) that focuses on Artificial Intelligence
helping machines understand and interpret visual information like images
and videos. While AI works to make machines think like humans, Computer Machine Learning
Vision gives them the ability to "see." This allows machines to observe,
Deep Learning
recognise patterns, and gather useful information from visual data, bringing
them closer to how humans perceive the world with their eyes.
Computer Vision Vs. Image Processing
Computer
It’s a common misconception that Computer Vision and Image Processing Vision
are the same because both deal with visual data such as images and videos.
However, they serve different purposes within the realm of technology and Artificial Intelligence (AI).
Let us learn the difference between Computer Vision and Image Processing.
Computer Vision Image Processing
Computer Vision enables machines to understand and Image processing involves manipulating and
interpret visual information, such as identifying objects, enhancing images to improve their quality or
recognising patterns, or making decisions based on visual extract specific features. It focuses on the technical
inputs. It focuses on extracting high-level information to manipulation of raw image data.
mimic human vision. For example, Rescaling Images, Correcting
For example, Object Detection, Handwriting Recognition, Brightness, Changing Tones, Enhancing Edges, etc.
Facial Recognition, etc.
194 Artificial Intelligence Play (Ver 1.0)-X

