Subjective Quality Assessment of the Impact of Buffer Size in Fine-Grain Parallel Video Encoding

Fine-Grain parallelism is essential for real-time video encoding performance. This usually implies setting a fixed buffer size for each encoded block. The choice of this parameter is critical for both performance and hardware cost. In this paper we analyze the impact of buffer size on image subjective quality, and its relation with other encoding parameters. We explore the consequences on visual quality, when minimizing buffer size to the point of causing the discard of quantized coefficients for highest frequencies. Finally, we propose some guidelines for the choice of buffer size, that has proven to be heavily dependent, in addition to other parameters, on the type of sequence being encoded. These guidelines are useful for the design of efficient realtime encoders, both hardware and software

Relating Objective and Subjective Performance Measures for AAM-based Visual Speech Synthesizers

We compare two approaches for synthesizing visual speech using Active Appearance Models (AAMs): one that utilizes acoustic features as input, and one that utilizes a phonetic transcription as input. Both synthesizers are trained using the same data and the performance is measured using both objective and subjective testing. We investigate the impact of likely sources of error in the synthesized visual speech by introducing typical errors into real visual speech sequences and subjectively measuring the perceived degradation. When only a small region (e.g. a single syllable) of ground-truth visual speech is incorrect we find that the subjective score for the entire sequence is subjectively lower than sequences generated by our synthesizers. This observation motivates further consideration of an often ignored issue, which is to what extent are subjective measures correlated with objective measures of performance? Significantly, we find that the most commonly used objective measures of performance are not necessarily the best indicator of viewer perception of quality. We empirically evaluate alternatives and show that the cost of a dynamic time warp of synthesized visual speech parameters to the respective ground-truth parameters is a better indicator of subjective quality

An Anthropocentric Approach to Text Extraction from WWW Images

There is a significant need to analyse the text in images on WWW pages, both for effective indexing and for presentation by non-visual means (e.g., audio). This paper argues that the extraction of text from such images benefits from an anthropocentric approach in the distinction between colour regions. The novelty of the idea is the use of a human perspective of colour perception in preference to RGB colour space analysis. This enables the extraction of text in complex situations such as in the presence of varying colour and texture (characters and background). More precisely, characters are extracted as distinct regions with separate chromaticity and/or luminance by performing a layer decomposition of the image. The method described here is the first in our systematic approach to approximate the human colour perception characteristics for the identification of character regions. In this instance, the image is decomposed by performing histogram analysis of Hue and Luminance and merging in the HLS colour space

Conjoining the Concepts of Visitor Attitude and Place Image to Better Understand Casino Patrons\u27 Behavioral Intentions

The importance of visitor attitude and place image in understanding individual’s visit behavioral intention has both been emphasized in tourism literature. However, the two concepts seem to have been amalgamated; their distinctive and interactive roles are rarely discussed. To fill this gap, this study investigated visitor attitude from two different aspects in the context of casino gaming – one’s generic attitude versus specific attitude. A conjoined conceptual model based on the theories of planned behavior and place image is developed and empirically tested in the context of casinos in Central Indiana. The results indicate that ‘generic attitude,’ ‘specific attitude’ and ‘cognitive image’ all play significant and distinctive roles in the process of formulating visitor’s behavioral intention. The theoretical and practical implications of this study are discussed

Enhanced associations with actions of the artist influence gaze behaviour

The aesthetic experience of the perceiver of art has been suggested to relate to the art-making process of the artist. The artist’s gestures during the creation process have been stated to influence the perceiver’s art-viewing experience. However, limited studies explore the art-viewing experience in relation to the creative process of the artist. We introduced eye-tracking measures to further establish how congruent actions with the artist influence perceiver’s gaze behaviour. Experiments 1 and 2 showed that simultaneous congruent and incongruent actions do not influence gaze behaviour. However, brushstroke paintings were found to be more pleasing than pointillism paintings. In Experiment 3, participants were trained to associate painting actions with hand primes to enhance visuomotor and visuovisual associations with the artist’s actions. A greater amount of time was spent fixating brushstroke paintings when presented with a congruent prime compared with an incongruent prime, and fewer fixations were made to these styles of paintings when presented with an incongruent prime. The results suggest that explicit links that allow perceivers to resonate with the artist’s actions lead to greater exploration of preferred artwork styles

A statistical reduced-reference method for color image quality assessment

Although color is a fundamental feature of human visual perception, it has been largely unexplored in the reduced-reference (RR) image quality assessment (IQA) schemes. In this paper, we propose a natural scene statistic (NSS) method, which efficiently uses this information. It is based on the statistical deviation between the steerable pyramid coefficients of the reference color image and the degraded one. We propose and analyze the multivariate generalized Gaussian distribution (MGGD) to model the underlying statistics. In order to quantify the degradation, we develop and evaluate two measures based respectively on the Geodesic distance between two MGGDs and on the closed-form of the Kullback Leibler divergence. We performed an extensive evaluation of both metrics in various color spaces (RGB, HSV, CIELAB and YCrCb) using the TID 2008 benchmark and the FRTV Phase I validation process. Experimental results demonstrate the effectiveness of the proposed framework to achieve a good consistency with human visual perception. Furthermore, the best configuration is obtained with CIELAB color space associated to KLD deviation measure