Improve performance of dense optical flow analysis (easily)?

I wrote a program that uses OpenCV's cvCalcOpticalFlowLK. It performs fine on a low-resolution webcam input, but I need to run it on a full HD stream with significant other computation following the optical flow analysis for each frame. Processing a 5 minute video scaled down to 1440x810 took 4 hours :( Most of the time is being spent in cvCalcOpticalFlowLK.

I've researched improving the speed by adding more raw CPU, but even if I get an 8-core beast, and the speedup is the theoretical ideal (say 8x, since I'm basically only using one of my 2.9GHz cores), I'd only be getting 4FPS. I'd like to reach 30FPS.

More research seems to point to implementing it on the GPU with CUDA, OpenCL, or GLSL(?). I've found some proof-of-concept implementations (eg. http://nghiaho.com/?page_id=189), and many papers saying basically "it's a great application for the GPU, we did it, it was awesome, and no we won't share our code". Needless to say, I haven't gotten any of them to run.

Does anyone know of a GPU开发者_如何学C-based implementation that would run on Mac with an NVIDIA card? Are there resources that might help me approach writing my own? Are there other dense OF algorithms that might perform better?

Thanks!

What about OpenVidia Bayesian Optical Flow? Also the paper Real-Time Dense and Accurate Parallel Optical Flow using CUDA says that their work is freely available in the CUDA zone. I couldn't find it there immediately, but maybe you will, or can write the authors?