Final year Projects for Information Technology

Final year Projects for Information Technology in Networking

Final year Projects for Information Technology

• Real-time Person Tracking in High-resolution Panoramic Video for Automated Broadcast Production
  For enabling immersive user experiences for interactive TV services and automating camera view selection and framing, knowledge of the location of persons in a scene is essential. We describe an architecture for detecting and tracking persons in high-resolution panoramic video streams, obtained from the Omni Cam, a panoramic camera stitching video streams from 6 HD resolution tiles. We use a CUDA accelerated feature point tracker, a blob detector and a CUDA HOG person detector, which are used for region tracking in each of the tiles before fusing the results for the entire panorama. In this paper we focus on the application of the HOG person detector in real-time and the speedup of the feature point tracker by porting it to NVIDIA's Fermi architecture. Evaluations indicate significant speedup for our feature point tracker implementation, enabling the entire process in a real-time system. …
• Automatic panorama generation from a video with dynamic background
  Panorama photos are very useful when capturing large scenic backgrounds like famous constructions or eye catching landscapes. Users normally prefer capturing such backgrounds with them or friends as the foreground, but the moving people in such popular locations always obstruct the iconic structure in the background. In this paper a solution for automatic panorama generation is presented which is capable of removing moving objects in the background. First user captures a short video starting from the centre of the focus area and then following a clockwise circular path. The proposed application generates the panorama based on input video following the steps: segmentation of human object, removal of moving human objects, and generation of panorama. Experimental output panorama photos show that the proposed system is very usable and results are satisfactory. …
• The Next Grand Challenges: Integrating the Internet of Things and Data Science
  While Chaos Engineering has gained currency in the Site Reliability Engineering community, service and business owners are often nervous about experimenting in production. Proving the benefits of Chaos Engineering to these stakeholders before implementing a program can be challenging. We present the business case for Chaos Engineering, through both qualitative and quantitative tactics, as well as the benefits and tools to convince stakeholders this is necessary and cost-efficient. …
• CUP: A Formalism for Expressing Cloud Usage Patterns for Experts and Non-Experts
  The proliferation of cloud services, from infrastructure servers to software, has led to patterns in service deployment and provisioning practices, but not to standards for expressing and communicating such patterns to a broad-based audience. To enable the formal description and pattern classification of scenarios where cloud services are combined and provisioned to end-users, we propose a textual and visual formalism - the Cloud Usage Patterns (CUP) formalism. With CUP, both general users and cloud experts can express patterns. By expressing patterns seen in practice, we demonstrate that CUP is practically useful and makes the use of lengthy prose descriptions obsolete, which is currently common and often results in misunderstandings. …
• A Combinatorial Auction Mechanism for Multiple Resource Procurement in Cloud Computing
  In hybrid cloud computing, cloud users have the ability to procure resources from multiple cloud vendors, and furthermore also the option of selecting different combinations of resources. The problem of procuring a single resource from one of many cloud vendors can be modeled as a standard winner determination problem, and there are mechanisms for single item resource procurement given different QoS and pricing parameters. There however is no compatible approach that would allow cloud users to procure arbitrary bundles of resources from cloud vendors. We design the cloud - CABOB algorithm to solve the multiple resource procurement problem in hybrid clouds. Cloud users submit their requirements, and in turn vendors submit bids containing price, QoS and their offered sets of resources. The approach is scalable, which is necessary given that there are a large number of cloud vendors, with more continually appearing. We perform experiments for procurement cost and scalability efficacy on the cloud - CABOB algorithm using various standard distribution benchmarks like random, uniform, decay and CATS. Simulations using our approach with prices procured from several cloud vendors’ datasets show its effectiveness at multiple resource procurement. …