Computer Vision(CV) is a field of Artificial Intelligence(AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs- and make recommended output based on that.
If AI enables computers to think, computer vision enables them to see, observe and understand.
CV trains their machine to do such work but it should do those work in lesser time with the use of cameras or algorithms as compare to retina or nerves.
According to report- the market of CV continuing to grow. It is expected to reach USD 48.6 billion by 2022.
Computer vision requires lots of data for getting good accuracy.
Two essential technologies are used to accomplish this: a type of machine learning called deep learning and a convolutional neural network (CNN) but now a days there are many pre-made libraries and frameworks available where you need not to know CNN or RNN.
For eg: openCV
There are many research has done in this field, but apart from it there are many uses of CV in business, entertainment, transportation, healthcare and everyday life.
eg: Google translate let you point your camera at a sign in another language almost immediately.
- Image Classification: It sees an image and can classify it (a dog, an apple, a person’s face).
- Object detection: It can use image classification to identify a certain class of image and then detect and tabulate their appearance in an image or video.
- Object Tracking: It follows or tracks an object once it is detected. This task is executed by with image capturing in sequence or real-time.
- Content-based image retrieval: It uses computer vision to browse, search and retrieve images from large data stores, based on the content of the images rather than metadata tags associated with them.(PS:This is most useful application of CV)
Now it's time to explore friends.
Thanks for reading.