Master of Science in Computer Science
First Committee Member
Ajoy K. Datta
Second Committee Member
Third Committee Member
Fourth Committee Member
Number of Pages
The need for parallelism is growing with the broadening of computing in the real world where computing is an integral part of any field. In the early days of computing, adding transistors to the CPU could solve computation complexity. This is not the case now, where we can no longer advance the hardware capabilities at the pace of the advancement of computing problems. One of the fields which is intensive in computation is image processing. If it were just for one frame of an image, we could cope with the computation overhead. When the need is to compute video frames, in some cases real-time video analysis, sequential execution of each frame could delay the result. In this thesis, we propose a parallel implementation of computing video frames. In particular, we focus on detecting new static objects that arrive in the already defined static background. This has practical implications as well. In a traffic crossing which is prone to accidents, this can be used to detect a vehicle or person in distress. The sequential implementation of this is fairly simple. However, as this is a computation-intensive problem, it would be more efficient to design a parallel solution.
Distributed; Image; MPI; Parallel; Processing; Programming
Shiwakoti, Tirambad, "Parallel Static Object Detection" (2016). UNLV Theses, Dissertations, Professional Papers, and Capstones. 2739.