https://code.google.com/p/os6sense/downloads/list
I thought I'd upload my tracker, watch the video from yesterday for an example of the sort of performance to expect under optimal conditions! Optimal conditions means stable lighting, and removing elements of a similar colour to that which you wish to track. Performance is probably a little worse, (and at best similar to) the touchless SDK.
Under suboptimal conditions...well its useless but then so are most trackers which is a real source of complaint about most of the computer vision research out there.....not that they perform poorly but rather that there is far too little honesty in just how poorly various algorithms perform under non-laboratory conditions.
I've a few revisions to make to improve performance and stability and I'm not proud of the code. It's been...8 years since I last did anything with C++ and to be frank I'd describe this more as a hack. Once this masters is out of the way I plan to look at this again and try out some of my ideas but I really see any approach which relies on colour based segmentation and standard webcams as having limited applicability.
So its taken a while but I hope this proves of use to someone someone some day.
I thought I'd upload my tracker, watch the video from yesterday for an example of the sort of performance to expect under optimal conditions! Optimal conditions means stable lighting, and removing elements of a similar colour to that which you wish to track. Performance is probably a little worse, (and at best similar to) the touchless SDK.
Under suboptimal conditions...well its useless but then so are most trackers which is a real source of complaint about most of the computer vision research out there.....not that they perform poorly but rather that there is far too little honesty in just how poorly various algorithms perform under non-laboratory conditions.
I've a few revisions to make to improve performance and stability and I'm not proud of the code. It's been...8 years since I last did anything with C++ and to be frank I'd describe this more as a hack. Once this masters is out of the way I plan to look at this again and try out some of my ideas but I really see any approach which relies on colour based segmentation and standard webcams as having limited applicability.
So its taken a while but I hope this proves of use to someone someone some day.
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