Can small be beautiful? assessing image resolution requirements for mobile TV

Mobile TV services are now being offered in several countries, but for cost reasons, most of these services offer material directly recoded for mobile consumption (i.e. without additional editing). The experiment reported in this paper, aims to assess the image resolution and bitrate requirements for displaying this type of material on mobile devices. The study, with 128 participants, examined responses to four different image resolutions, seven video encoding bitrates, two audio bitrates and four content types. The results show that acceptability is significantly lower for images smaller than 168×126, regardless of content type. The effect is more pronounced when bandwidth is abundant, and is due to important detail being lost in the smaller screens. In contrast to previous studies, participants are more likely to rate image quality as unacceptable when the audio quality is high

Personalization of Saliency Estimation

Most existing saliency models use low-level features or task descriptions when generating attention predictions. However, the link between observer characteristics and gaze patterns is rarely investigated. We present a novel saliency prediction technique which takes viewers' identities and personal traits into consideration when modeling human attention. Instead of only computing image salience for average observers, we consider the interpersonal variation in the viewing behaviors of observers with different personal traits and backgrounds. We present an enriched derivative of the GAN network, which is able to generate personalized saliency predictions when fed with image stimuli and specific information about the observer. Our model contains a generator which generates grayscale saliency heat maps based on the image and an observer label. The generator is paired with an adversarial discriminator which learns to distinguish generated salience from ground truth salience. The discriminator also has the observer label as an input, which contributes to the personalization ability of our approach. We evaluate the performance of our personalized salience model by comparison with a benchmark model along with other un-personalized predictions, and illustrate improvements in prediction accuracy for all tested observer groups

Ergonomics of the Operative Field in Paediatric Minimal Access Surgery

Imperial Users onl