Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Major/Program

Computer Science

First Advisor's Name

Zhenyu Yang

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Peter Clarke

Third Advisor's Name

Christine Lisetti

Fourth Advisor's Name

Deng Pan

Fifth Advisor's Name

Chen Liu

Keywords

Multimedia, Quality of Experience, Quality of Service, Image Enhancement, Affective Computing, VoIP, Machine Learning

Date of Defense

7-13-2012

Abstract

The multimedia domain is undergoing a rapid development phase with transition in audio, image, and video systems such as VoIP, Telepresence, Live/On-Demand Internet Streaming, SecondLife, and many more. In such a situation, the analysis of multimedia systems, like retrieval, quality evaluation, enhancement, summarization, and re-targeting applications, from various context is becoming critical. Current methods for solving the above-mentioned analysis problems do not consider the existence of humans and their affective characteristics in the design methodology. This contradicts the fact that most of the digital media is consumed only by the human end-users. We believe incorporating human feedback during the design and adaptation stage is key to the building process of multimedia systems. In this regard, we observe that affect is an important indicator of human perception and experience. This can be exploited in various ways for designing effective systems that will adapt more closely to the human response.

We advocate an affect-based modeling approach for solving multimedia analysis problems by exploring new directions. In this dissertation, we select two representative multimedia analysis problems, e.g. Quality-of-Experience (QoE) evaluation and Image Enhancement in order to derive solutions based on affect-based modeling techniques. We formulate specific hypothesis for them by correlating system parameters to user's affective response, and investigate their roles under varying conditions for each respective scenario. We conducted extensive user studies based on human-to-human interaction through an audio conferencing system.We also conducted user studies based on affective enhancement of images and evaluated the effectiveness of our proposed approaches. Moving forward, multimedia systems will become more media-rich, interactive, and sophisticated and therefore effective solutions for quality, retrieval, and enhancement will be more challenging. Our work thus represents an important step towards the application of affect-based modeling techniques for the future generation of multimedia systems.

Identifier

FI12081301

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