Assessing the use of Photorealistic and Computer Simulated Landscapes to Understand the Cumulative Landscape and Visual Impacts of Onshore Wind Turbines

There has been considerable research into issues around the social acceptance and visual impact of wind farms. However, relatively little is known about the factors that contribute to the cumulative landscape and visual impacts (CLVI) of wind turbines. With the continued growth of onshore wind power in the UK, understanding the CLVI of wind power developments is increasingly important. The majority of research which has studied the landscape and visual impact of wind turbines has used static photomontages. Some researchers have suggested that computer simulations should be used for research, as well as interactive design and planning. However, little if any research has been done which objectively assesses the validity of using these simulations. This thesis set out to address these methodological and theoretical gaps in the literature. Chapters 3 and 4 present two studies that were carried out to assess physiological responses to videos of wind turbines in a real-world and computer-simulated landscape (created using Sketchup and Google Earth). The findings showed that participants’ visual patterns were similar for the photorealistic and computer-simulated landscape, however the skin conductance response (SCR) data showed that affective responses were quite different. Given the different in affective response, these studies called into question the validity of using computer simulations to represent wind turbines in the landscape. Chapter 5 presents a study which attempted to examine whether the differences found in studies 1 and 2 were of any practical significance. As such, it sought to examine if there were any differences in preferences based on whether people were present with a photomontage or a computer simulation. The study also sought to better understand the factors that contribute to the CLVI of wind farm extensions. Results suggest that people’s preferences are not affected by whether they are presented with photomontages or computer simulations. The results also suggest that size, number, visual match, and turbine distribution are important factors in contributing to the visual impact of wind farm extensions. Collectively, the three studies illustrate novel methods for research into the CLVI of wind turbines. The studies also provide support for the use of computer simulations in research and interactive design and planning, as well as giving some insights into the factors that affect the CLVI of wind farm extensions

Privacy-Friendly Photo Sharing and Relevant Applications Beyond

Popularization of online photo sharing brings people great convenience, but has also raised concerns for privacy. Researchers proposed various approaches to enable image privacy, most of which focus on encrypting or distorting image visual content. In this thesis, we investigate novel solutions to protect image privacy with a particular emphasis on online photo sharing. To this end, we propose not only algorithms to protect visual privacy in image content but also design of architectures for privacy-preserving photo sharing. Beyond privacy, we also explore additional impacts and potentials of employing daily images in other three relevant applications. First, we propose and study two image encoding algorithms to protect visual content in image, within a Secure JPEG framework. The first method scrambles a JPEG image by randomly changing the signs of its DCT coefficients based on a secret key. The second method, named JPEG Transmorphing, allows one to protect arbitrary image regions with any obfuscation, while secretly preserving the original image regions in application segments of the obfuscated JPEG image. Performance evaluations reveal a good degree of storage overhead and privacy protection capability for both methods, and particularly a good level of pleasantness for JPEG Transmorphing, if proper manipulations are applied. Second, we investigate the design of two architectures for privacy-preserving photo sharing. The first architecture, named ProShare, is built on a public key infrastructure (PKI) integrated with a ciphertext-policy attribute-based encryption (CP-ABE), to enable the secure and efficient access to user-posted photos protected by Secure JPEG. The second architecture is named ProShare S, in which a photo sharing service provider helps users make photo sharing decisions automatically based on their past decisions using machine learning. The photo sharing service analyzes not only the content of a user's photo, but also context information about the image capture and a prospective requester, and finally makes decision whether or not to share a particular photo to the requester, and if yes, at which granularity. A user study along with extensive evaluations were performed to validate the proposed architecture. In the end, we research into three relevant topics in regard to daily photos captured or shared by people, but beyond their privacy implications. In the first study, inspired by JPEG Transmorphing, we propose an animated JPEG file format, named aJPEG. aJPEG preserves its animation frames as application markers in a JPEG image and provides smaller file size and better image quality than conventional GIF. In the second study, we attempt to understand the impact of popular image manipulations applied in online photo sharing on evoked emotions of observers. The study reveals that image manipulations indeed influence people's emotion, but such impact also depends on the image content. In the last study, we employ a deep convolutional neural network (CNN), the GoogLeNet model, to perform automatic food image detection and categorization. The promising results obtained provide meaningful insights in design of automatic dietary assessment system based on multimedia techniques, e.g. image analysis