Know Top Computer Vision Trends to Adopt in 2022

Computer vision trends are set to dominate the global tech industry in 2022

Thanks to the recent technological advancements in artificial intelligence and innovations in deep learning, computer vision has become a powerful tool driving transformation in industries. Computer vision is the part of computer science that focuses on replicating parts of the complexity of the human vision and enables computers to identify objects and visuals the same way humans do. 

Computer vision plays an important role in facial recognition applications. This technology enables computers to match images of people's faces to get their identities. Computer vision algorithms detect facial features in images and compare them with databases of information. Computer vision also plays an important role in augmented reality and virtual reality, the technology that enables computing devices such as smartphones, tablets, and smart glasses to overlay embed virtual objects on real world imagery. 

Computer vision is a thrilling technology. Even supercomputers might take days, weeks, or even months to perform their jobs, but this technology is related to chips and hardware which makes it speedy, along with cloud networks, it gets a lightning speed.

Computer vision trends:

• Advances in Deep Learning: Deep learning has gained popularity for delivering accurate results. Deep learning algorithms can be used to train the machines to accurately identify images and videos. It has reduced laborious tasks including annotating and labeling data. 

• Object Recognition with Point Cloud: Point cloud is frequently used for object recognition and object tracking. It is a collection of data points defined within three-dimensional coordinate system. It provides accurate representation of an object in any space or movement. 

• Semantic Instance Segmentation: Semantic and instance segmentation is a powerful tool which can detect all pixels belonging to objects in a picture. It can also determine what pixels belong to which objects and where is the object located in the picture. 

• Merged Reality-AR and VR enhanced: Computer vision technology is pushing AR and VR to a next level development, creating MR (Merged Reality). AR and VR technologies can create a 3D environment to track an object's movement in the picture. 

• Edge Computing: Edge computing solves the problem of network accessibility and latency. For computer vision, it can be used to respond better with accurate real-time results.