Finally, we evaluate six state-of-the-art trackers on the TSV dataset and analysis their performance with regard of transcoding parameters. Then, we design a framework for assessing the performance of trackers. To address this, first, a large-scale transcoding surveillance video (TSV) dataset is constructed. Consequently, in this paper, we evaluate the impact of video transcoding parameters on the performance of visual object tracking algorithms. However, since the transcod-ing operation is a lossy process, this can effect the performance of video analysis techniques such as visual object tracking. To meet this adaptability requirement, the video transcoding process is inevitable, which consists of converting a video from one compressed format to another. In any video surveillance system, it is very important to provide effective remote viewing to heterogeneous users with various network conditions and viewing device. Also, a strong correlation between the objective and subjective measurements was found, but the speed at which the objective and subjective measurements were changing, is different. By analyzing the subjective results we found that the participants interpreted VD quality at 0.5% PLR and higher in a similar way, except when they were watching a video where the participants rated their experience lower with every increase in PLR value. The results show that the packet loss rate (PLR) impacts the zero client performance based on the application with streaming videos experienced the highest impact. Therefore, we introduce a new metric and methodology to measure zero client VD performance based on analyzing network traffic, and conducted objective and subjective studies to determine the sensitivity of zero client computing to different network conditions.
MEDIA PLAYER CODEC PACK 4.3.6 SOFTWARE
Unlike most virtual desktop environments, zero clients are not able to run monitoring software at the client, complicating performance assessments. We measured the performance of VDs accessed through zero clients to study the feasibility of using this approach to provide a desktop-PC experience across a network. Zero clients are hardware-based computing devices and interfaces without a central processing unit (CPU), that provide a computing user experience and functionality through Virtual Desktops (VDs) delivered from remote computing infrastructure.
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