OS6Sense

Yes, we have a video! http://www.youtube.com/watch?v=GXlmus93o68 I wasn't intending to work on any code this weekend but I felt compelled to try out the recognition server and run another set of tests but with the Logitech C900 in place. Results were an improvement on the PS3 eye, in part due to the better low light capabilities, in part due to the camera placement, and in part due to the wider angle. Some anecdotal notes : The recognition server provided seems to perform better that the unistroke implementation - I still need to sit down and do the numbers but I wouldn't be surprised if it wasn't significantly better. I suspect recall for all but the most basic figures/shapes provided via the default unistroke implementation will be poor amongst users. On the flip side, most of us know the alphabet! Big problem with the use of fiducials on the end of the fingers - they become obscured during natural hand movements! I ended up cupping the marker in my hand and s

Just an update - while I had originally approached this with the intention of releasing the code as open source my findings regarding....well various aspects of this project, but relevant to this aim, the code itself, means that I'm putting any software development on the back burner for the next few weeks while I perform a study into how people naturally perform gestures. I'm also looking at some options to improve certain show stopping issues with the system (primarily the limited FOV of the webcam). Any code that does emerge for the project, at least for version 0.1 is unlikely to be very robust but I think that can be overcome : I'm currently thinking that broad colour segmentation followed by some form of object matching technique (e.g. SIFT/SURF) should make quite a robust and reasonably fast algorithm for marker detection however if the FOV problem cant be solved, I actually think that ANY vision based system is inappropriate for this sort of interaction style. Y

Children back at school and I'm back off my hols (a rather interesting time in Estonia if you're interested). I've spent most of the last week becoming increasingly frustrated with my attempts at image segmentation. I've moved to a c++ implementation for speed and, while the VERY simplistic HSV segmentation technique I am using works, the problem is that I cannot get it to work robustly and doubt that it will ever do such. I've now covered the range of available techniques and even tried to plumb the depths of just emerging ones and it seems that every computer vision based object tracking implementation or algorithm suffers for the same issue with robustness (openTLD, camshift, touchless, hsv segmentation and cvBlob etc etc). YES, it can be made to work, but issues include (depending on the algorithm) : - Object drift : over time the target marker will cease to be recognised and other objects will become the target focus. - Multiple objects : During segments