The mosaic test:benchmarking colour-based image retrieval systems using image mosaics

Evaluation and benchmarking in content-based image retrieval has always been a somewhat neglected research area, making it difficult to judge the efficacy of many presented approaches. In this paper we investigate the issue of benchmarking for colour-based image retrieval systems, which enable users to retrieve images from a database based on lowlevel colour content alone. We argue that current image retrieval evaluation methods are not suited to benchmarking colour-based image retrieval systems, due in main to not allowing users to reflect upon the suitability of retrieved images within the context of a creative project and their reliance on highly subjective ground-truths. As a solution to these issues, the research presented here introduces the Mosaic Test for evaluating colour-based image retrieval systems, in which test-users are asked to create an image mosaic of a predetermined target image, using the colour-based image retrieval system that is being evaluated. We report on our findings from a user study which suggests that the Mosaic Test overcomes the major drawbacks associated with existing image retrieval evaluation methods, by enabling users to reflect upon image selections and automatically measuring image relevance in a way that correlates with the perception of many human assessors. We therefore propose that the Mosaic Test be adopted as a standardised benchmark for evaluating and comparing colour-based image retrieval systems

The mosaic test:measuring the effectiveness of colour-based image retrieval

A variety of content-based image retrieval systems exist which enable users to perform image retrieval based on colour content - i.e., colour-based image retrieval. For the production of media for use in television and film, colour-based image retrieval is useful for retrieving specifically coloured animations, graphics or videos from large databases (by comparing user queries to the colour content of extracted key frames). It is also useful to graphic artists creating realistic computer-generated imagery (CGI). Unfortunately, current methods for evaluating colour-based image retrieval systems have 2 major drawbacks. Firstly, the relevance of images retrieved during the task cannot be measured reliably. Secondly, existing methods do not account for the creative design activity known as reflection-in-action. Consequently, the development and application of novel and potentially more effective colour-based image retrieval approaches, better supporting the large number of users creating media for use in television and film productions, is not possible as their efficacy cannot be reliably measured and compared to existing technologies. As a solution to the problem, this paper introduces the Mosaic Test. The Mosaic Test is a user-based evaluation approach in which participants complete an image mosaic of a predetermined target image, using the colour-based image retrieval system that is being evaluated. In this paper, we introduce the Mosaic Test and report on a user evaluation. The findings of the study reveal that the Mosaic Test overcomes the 2 major drawbacks associated with existing evaluation methods and does not require expert participants

Emotional bias training as a treatment for anxiety and depression:evidence from experimental medicine studies in healthy and medicated samples

BACKGROUND: Anxiety and depression are leading causes of disability worldwide, yet individuals are often unable to access appropriate treatment. There is a need to develop effective interventions that can be delivered remotely. Previous research has suggested that emotional processing biases are a potential target for intervention, and these may be altered through brief training programs. METHODS: We report two experimental medicine studies of emotional bias training in two samples: individuals from the general population (n = 522) and individuals currently taking antidepressants to treat anxiety or depression (n = 212). Participants, recruited online, completed four sessions of EBT from their own home. Mental health and cognitive functioning outcomes were assessed at baseline, immediately post-training, and at 2-week follow-up. RESULTS: In both studies, our intervention successfully trained participants to perceive ambiguous social information more positively. This persisted at a 2-week follow-up. There was no clear evidence that this change in emotional processing transferred to improvements in symptoms in the primary analyses. However, in both studies, there was weak evidence for improved quality of life following EBT amongst individuals with more depressive symptoms at baseline. No clear evidence of transfer effects was observed for self-reported daily stress, anhedonia or depressive symptoms. Exploratory analyses suggested that younger participants reported greater treatment gains. CONCLUSIONS: These studies demonstrate the effectiveness of delivering a multi-session online training program to promote lasting cognitive changes. Given the inconsistent evidence for transfer effects, EBT requires further development before it can be considered as a treatment for anxiety and depression

Cognitive bias modification for facial interpretation:A randomized controlled trial of transfer to self-report and cognitive measures in a healthy sample

Cognitive bias modification is a potential low-intensity intervention for mood disorders, but previous studies have shown mixed success. This study explored whether facial interpretation bias modification (FIBM), a similar paradigm designed to shift emotional interpretation (and/or perception) of faces would transfer to: (i) self-reported symptoms and (ii) a battery of cognitive tasks. In a preregistered, double-blind randomized controlled trial, healthy participants received eight online sessions of FIBM (N = 52) or eight sham sessions (N = 52). While we replicate that FIBM successfully shifts ambiguous facial expression interpretation in the intervention group, this failed to transfer to the majority of self-report or cognitive measures. There was, however, weak, inconclusive evidence of transfer to a self-report measure of stress, a cognitive measure of anhedonia, and evidence that results were moderated by trait anxiety (whereby transference was greatest in those with higher baseline symptoms). We discuss the need for work in both larger and clinical samples, while urging caution that these FIBM training effects may not transfer to clinically relevant domains

The 2dF Galaxy Redshift Survey: spectral types and luminosity functions

We describe the 2dF Galaxy Redshift Survey (2dFGRS) and the current status of the observations. In this exploratory paper, we apply a principal component analysis to a preliminary sample of 5869 galaxy spectra and use the two most significant components to split the sample into five spectral classes. These classes are defined by considering visual classifications of a subset of the 2dF spectra, and also by comparison with high-quality spectra of local galaxies. We calculate a luminosity function for each of the different classes and find that later-type galaxies have a fainter characteristic magnitude, and a steeper faint-end slope. For the whole sample we find M*=−19.7 (for Ω=1, H₀=100 km s⁻¹ Mpc⁻¹), α=−1.3, φ*=0.017. For class 1 (‘early-type’) we find M*=−19.6, α=−0.7, while for class 5 (‘late-type’) we find M*=−19.0, α=−1.7. The derived 2dF luminosity functions agree well with other recent luminosity function estimates