Computer vision is notoriously tricky and challenging. It aims to build autonomous systems that can perform or even surpass the tasks associated with the human visual system, but what makes it extremely difficult to build such a system is because the human visual system is too good and sophisticated for many tasks in comparison with a computer vision system.
Humans can recognize faces under all variations in terms of illumination, viewpoint, or expression. In most cases, we have no problem in identifying a friend in an old photograph taken years ago. There seems to be no limit for us on how many faces we can store in our brains for future recognition. There seems no hope in building an autonomous system with such stellar performance.
Though it was somewhat disappointing, computer vision has been offering several exciting applications in healthcare, manufacturing, defense, etc. Medical image processing is one most common application, where the data is extracted from images, such as microscopy images, X-ray images, angiography images, ultrasonic images, and tomography images, for the medical diagnosis of patients. It helps detect tumors, arteriosclerosis, or other malign changes and measure organ dimensions, blood flow, etc.
In manufacturing, computer vision is heavily used to find defects and measure the position and orientation of products to be picked up by a robot arm. The military applications include the detection of enemy soldiers or vehicles, missile guidance, and creating battlefield awareness about a combat scene to reduce complexity and to fuse information from multiple sensors for supporting strategic decisions.
All levels of autonomy, ranging from semi-autonomous to fully autonomous vehicles such as submersibles, land-based robots, cars, trucks, UAVs, use computer vision-based systems to support drivers/pilots in various situations. They use it for navigation through its environment (SLAM), detecting obstacles and specific events, like forest fires.
Curious to know more about computer vision? Below, you can find 50 useful research papers and resources to get started with computer vision and applications. Feel free to download. Share your own research papers with us to be added to this list.
- Computer Vision and Applications – A Guide for Students and Practitioners
- Introduction to Computer Vision
- An Introduction to Computer Vision – Northwestern University
- What is computer vision
- Machine Vision for Precision Agriculture
- Testing Computer Vision Applications – An Experience Report on Introducing Code Coverage Analysis
- Computer Vision: Application in Embedded System
- Introductory techniques for 3-D computer vision
- Introduction to Computer Vision from Automatic Face Analysis
- Computer Vision: 16 Lectures by J G Daugman
- Real-time computer vision with OpenCV
- Reconfiguring the Imaging Pipeline for Computer Vision CVF
- Machine Learning saves Computer Vision
- Where computer vision needs help from computer science
- Computer Vision-Based Descriptive Analytics of Seniors Daily
- Programming Computer Vision with Python
- Computer Vision: Algorithms and Applications
- Computer vision and fuzzy-neural systems
- Computer Vision:Foundations and Applications Stanford
- CAGD-based computer vision
- OpenCV 3 Computer Vision Application Programming
- The Three Rs of Computer Vision
- Computer Vision and Deep Learning for Remote Sensing
- Handbook of Computer Vision and Applications X-Files
- Computer Vision and Image Processing
- Ethical issues in topical computer vision applications
- A hardware-software architecture for computer vision systems
- A polyhedron representation for computer vision
- Applications of parametric maxflow in computer vision
- Face recognition by humans: Nineteen results all computer vision researchers should know about
- Efficient graph-based energy minimization methods in computer vision
- Machine Learning in Computer Vision
- Computer Vision Introduction Outlines CS Rutgers
- Computer Vision: Image Features
- Fundamentals of Computer Vision
- The Lighting And Optics Expert System For Machine Vision
- Computer vision for computer games
- Computer vision for computer interaction
- Structured Learning and Prediction in Computer Vision Now
- Elastica and computer vision
- A robust competitive clustering algorithm with applications in computer vision
- Exploring Computer vision in Deep Learning: Object Detection and
- Computer Vision based Fire Detection System Sasken
- Reliable Vision Application Development
