tracking.js is a new library that intends to bring the power of computer vision to the Web. OpenCV is far older and is a inspiration for our team regarding the number of available algorithms, robustness and speed. With the increasing power of JavaScript engines, we believe that we can achieve very good results using current state-of-the-art algorithms and low-level optimizations, so real-time CV applications can also be done on the Web.
Currently tracking.js don't have as many algorithms as OpenCV, but we are making our best efforts to bring useful algorithms to the library while still keeping the API easy to use and to extend, so we can count on the community to help us to make this project a success.
Great. This is actually very relevant to a project I'm working on. It involves porting projecter/camera electronics from open cv over to the web with javascript. So how does this stack up vs jsfeat? Are those comparable at all? I do think your api is more web dev friendly from what it looks like, but I am curious about the capabilities.
One of the biggest problems we find on most computer vision libraries is the fact that a lot of knowledge in the area is required to use them properly. We think the complex APIs that are exposed to developers that try to make CV apps can be the reason why we still don't see many apps exploring the potential of CV. So tracking.js was created with the goal of being as powerful as the best CV libraries, but without exposing the inherent complexity of the area to the developers that wish to use it. From what I saw of jsfeat, it looks very powerful, but targeted for people that have some knowledge of CV.
