Definition: Computer Vision is the field of computer science that helps the computers to gain high-level information from digital images and videos by analyzing them using various machine learning algorithms. From an engineering point of view, its main objective is to automate the human visual system and to lessen the human effort.
As a scientific discipline, computer vision is related to artificial systems. Computer vision image data can take many forms such as views from multiple cameras, multidimensional data from medical scanner or video frames etc.
Computer vision began in the late 1960s at universities which were pioneering in the field of artificial intelligence. It was developed to mimic the human visual system and was the next stepping stone towards building robots with their own human-like intelligence. This was first achieved in 1966 when a camera was attached to a computer and the computer was made to describe what it saw. …
· Jupyter Notebook which is a part of Anaconda3–2020.02 for Windows_x86 64 bit version was used for compilation purposes for this project with Python 3.7.6 installed on the device.
· The code was written in Python which is a high level, interpreted programming language. Libraries/ modules used will be mentioned below.
· The camera is assumed to be static.
· It does not have any automatic regulations such as auto focus etc.
· The user is not moving in the frame. (he can sit anywhere near the laptop but shouldn’t appear in the detection frame)
· Color constraints for the background are not there but presumably it should be static. (no moving objects or colors changing in the background of the frame. …
Human Computer Interaction (HCI) studies the design and use of computer technology particularly on interaction/ interfaces between the computer and the humans.
Since 1950s, scientist have been trying to make computers that can make sense from visual data inputs. In 2012 a major breakthrough was achieved when an AI system, AlexNet won the ImagNet computer vision contest with 85% accuracy. At the core of AlexNet was an already existing technology- Convolution Neural Network, that had not been used to its full potential in this field of computer vision.
Convolution Neural Network (CNN) also known as ConvNets were developed in 1980s and its early versions were called LeNet (after Le Cun). These networks were only used in niches of the banking and postal industry. Their main problem was scaling, they required large amounts of training data that wasn’t available at that time. …