Detecting scene changes in videos using CUDA and OpenCV.

CUDA is a parallel computing platform and application programming interface (API) model created by Nvidia. It allows software developers and software engineers to use a CUDA-enabled graphics processing unit (GPU) for GPGPU (General-Purpose computing on Graphics Processing Units).

OpenCV stands for Open Source Computer Vision Library. It has C++, python and Java interfaces.

The scene change detection problem is can be defined formally as - given two frames, do they belong to the same scene, or different scenes? The content-aware scene change detection finds all areas in a video where the difference between two subsequent frames exceeds a threshold value. This allows to detect cuts between scenes.

The proposed algorithm has the following steps - * Decode the video. * For each frame -

       * Convert the frame to HSV colour space.
       * For each channel, find the average pixel by pixel difference with the previous frame
       * Average the difference over the number of channels.
       * If greater than a given threshold declare the frame as a scene change

The pixel-by-pixel operation of each channel can be optimised to execute in parallel. This can be achieved using CUDA.

The simple algorithm above can be optimised to execute on a GPU and achieve 10x improvements in speed.

All the code is written in C++