Internet access has evolved in the last decade with the availability of smart handheld devices and high bandwidth offered by mobile networks at reduced costs. Multimedia traffic primarily video became the main share of global Internet traffic due to the popularity of multimedia supported social applications, online gaming, and IPTV. Thus, the success of any network based business model is dependent on service quality and Quality of Experience (QoE) is widely accepted as a means to describe user satisfaction with a service. QoE can be influenced by numerous factors ranging from content liking to system and context-related artifacts.

In this thesis, a holistic approach is adopted to evaluate the QoE of an end-user regarding video quality based on system, contextual and human factors. At the system level, an impact of the Maximum Transmission Unit (MTU), and the comparison of widely used video codecs in error-prone networks is investigated by using diverse streaming protocols on an emulated network. It is found that the myth of using small MTU for better performance in high-loss scenarios comes at a cost of increased latency at the intermediate nodes and doesn’t provide any gain in video quality. The performance of the Google royalty-free VP8 codec was also shown to be on par with the widely adopted and proprietary H.264, especially in scenarios involving high jitter. At a human level, user delight towards the shown stimulus, his or her mood along with the frequency of watching online content (contextual), and their impact on quality ratings are investigated. It is found that human-related personality traits tend to influence subjective ratings and highlight the requirement of more cohesive QoE models to estimate user perception.

The future trend of internet usage increasingly emphasizes visual modes of engagement and user interactions across complex scenarios, including multimedia video, gaming, mapping services, and immersive applications. Consequently, the success of media creators, application developers, and service providers hinges on selecting appropriate tools and technologies to optimize the user experience. Quality of Experience (QoE) offers a framework for evaluating user experience and satisfaction with applications or services by using both objective and subjective metrics. It is important to recognize that various factors can influence user feedback, including different traits of human personality, interactions with systems, and the context in which they are used.

In this thesis, we adopt a holistic approach to evaluate the QoE for video quality and outdoor applications, focusing on system, human, and contextual influence factors. From a system perspective, we investigate the performance of widely implemented video codecs and propose more effective objective QoE metrics. The objective results are benchmarked against subjective outcomes to underscore their limitations in quantifying user experience, which is influenced by numerous factors beyond system-related aspects. Regarding human influence factors, our analysis encompasses user delight with the content presented, mood, gender, and the impact of eye-tracking on user assessments. A key observation is the critical importance of selecting stimuli that effectively engage users to accurately capture the true impact of user delight in the context of mobile gaming. For contextual factors, we examine the frequency of use and highlight the distinction between assumptions and actual experiences during user evaluations of outdoor activities. Our findings reveal the notable effects of these influence factors, particularly user delight, which demonstrated significant outcomes. The impact of visual attention on user behavior and subsequent ratings was also established. Furthermore, we identify limitations in existing QoE metrics and underscore the need for more cohesive QoE models that effectively engage users with mobility-driven applications or services that are not confined to multimedia streaming. These insights are drawn from several use cases reflecting the evolving ways in which users are interacting with systems nowadays. Our findings highlight the need for future QoE methodologies to evolve, by integrating the complex interplay of technical and human-centric variables. This evolution is essential to develop flexible, dynamic, and scalable solutions that cater to the demands of diverse applications.