Dynamic texture analysis and segmentation using deterministic partially self-avoiding walks

Dynamic texture is a recent field of investigation that has received growing attention from computer vision community in the last years. These patterns are moving texture in which the concept of selfsimilarity for static textures is extended to the spatiotemporal domain. In this paper, we propose a novel approach for dynamic texture representation, that can be used for both texture analysis and segmentation. In this method, deterministic partially self-avoiding walks are performed in three orthogonal planes of the video in order to combine appearance and motion features. We validate our method on three applications of dynamic texture that present interesting challenges: recognition, clustering and segmentation. Experimental results on these applications indicate that the proposed method improves the dynamic texture representation compared to the state of the art.

Female mating preferences and male coloration covary with water transparency in a Lake Victoria cichlid fish

Rapid speciation in Lake Victoria cichlid fish of the genus Pundamilia may be facilitated by sexual selection: female mate choice exerts sexual selection on male nuptial coloration within species and maintains reproductive isolation between species. However, declining water transparency coincides with increasingly dull coloration and increasing hybridization. In the present study, we investigated the mechanism underlying this pattern in Pundamilia nyererei, a species that interbreeds with a sister species in turbid but not in clear water. We compared measures of intraspecific sexual selection between two populations from locations that differ in water transparency. First, in laboratory mate-choice experiments, conducted in clear water and under broad-spectrum illumination, we found that females originating from turbid water have significantly weaker preferences for male coloration than females originating from clear water. Second, both the hue and body coverage of male coloration differ between populations, which is consistent with adaptation to different photic habitats. These findings suggest that the observed relationship between male coloration and water transparency is not mediated by environmental variation alone. Rather, female mating preferences are indicated to have changed in response to this variation, constituting the first evidence for intraspecific preference-trait co-evolution in cichlid fish. (C) 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 398-406.

Individual Differences in First and Fourth Year College Women’s Short Term Mating Strategy Preferences and Perceptions

Using survey methodology, a cross sectional study was undertaken to ascertain whether first and fourth year college women have different perceptions and behavior associated with short term mating preferences. It was hypothesized that after incurring significant negative or costly experiences associated with hooking up, fourth year women would prefer men who had qualities associated with a desired long term partner as opposed to characteristics associated with short term mating partners. The results were partially consistent with the hypothesis. Reported preferences in a desired partner and perspective on hooking up differ between first and fourth year groups. No difference was found between frequency and willingness to hookup between the two groups. The findings are explained in terms of evolutionary theory, social exchange theory, and sexual script concepts.

Individual differences in first and fourth year college women’s short term mating strategy preferences and perceptions

Using survey methodology, a cross sectional study was undertaken to ascertain whether first and fourth year college women have different perceptions and behavior associated with short term mating preferences. It was hypothesized that after incurring significant negative or costly experiences associated with hooking up, fourth year women would prefer men who had qualities associated with a desired long term partner as opposed to characteristics associated with short term mating partners. The results were partially consistent with the hypothesis. Reported preferences in a desired partner and perspective on hooking up differ between first and fourth year groups. No difference was found between frequency and willingness to hookup between the two groups. The findings are explained in terms of evolutionary theory, social exchange theory, and sexual script concepts.

Tariff-Specific Preferences and Their Influence on Price Sensitivity

For many services, consumers can choose among a range of optional tariffs that differ in their access and usage prices. Recent studies indicate that tariff-specific preferences may lead consumers to choose a tariff that does not minimize their expected billing rate. This study analyzes how tariff-specific preferences influence the responsiveness of consumers’ usage and tariff choice to changes in price. We show that consumer heterogeneity in tariff-specific preferences leads to heterogeneity in their sensitivity to price changes. Specifically, consumers with tariff-specific preferences are less sensitive to price increases of their preferred tariff than other consumers. Our results provide an additional reason why firms should offer multiple tariffs rather than a uniform nonlinear pricing plan to extract maximum consumer surplus.

Time Preferences and Environmental Concern: An Analysis of the Swiss ISSP 2010

This study analyzes the trend of environmental concern in Switzerland using data from the International Social Survey Program (ISSP) 1993, 2000, and 2010. First, we compare the observed trend with indicators of the intensity of public debate regarding the environment. The results show that both the number of articles dealing with environmental issues in print newspapers and the debates in the Swiss parliament strongly increased during the observed period. The ecological awareness of the population, however, remained constant over this time. Second, we scrutinize the "social basis" of environmental concern paying particular attention to individuals' time preferences. Third, we investigate the relationship between environmental concern and proenvironmental behavior, on the one hand, and the relation of concern and the acceptance of governmental regulations, on the other hand.

Predictors of satisfaction with treatment decision, decision-making preferences, and main treatment goals in patients with advanced cancer

Purpose This study investigated satisfaction with treatment decision (SWTD), decision-making preferences (DMP), and main treatment goals, as well as evaluated factors that predict SWTD, in patients receiving palliative cancer treatment at a Swiss oncology network. Patients and methods Patients receiving a new line of palliative treatment completed a questionnaire 4–6 weeks after the treatment decision. Patient questionnaires were used to collect data on sociodemographics, SWTD (primary outcome measure), main treatment goal, DMP, health locus of control (HLoC), and several quality of life (QoL) domains. Predictors of SWTD (6 = worst; 30 = best) were evaluated by uni- and multivariate regression models. Results Of 480 participating patients in eight hospitals and two private practices, 445 completed all questions regarding the primary outcome measure. Forty-five percent of patients preferred shared, while 44 % preferred doctor-directed, decision-making. Median duration of consultation was 30 (range: 10–200) minutes. Overall, 73 % of patients reported high SWTD (≥24 points). In the univariate analyses, global and physical QoL, performance status, treatment goal, HLoC, prognosis, and duration of consultation were significant predictors of SWTD. In the multivariate analysis, the only significant predictor of SWTD was duration of consultation (p = 0.01). Most patients indicated hope for improvement (46 %), followed by hope for longer life (26 %) and better quality of life (23 %), as their main treatment goal. Conclusion Our results indicate that high SWTD can be achieved in most patients with a 30-min consultation. Determining the patient’s main treatment goal and DMP adds important information that should be considered before discussing a new line of palliative treatment.

3D Intervertebral Disc Localization and Segmentation from MR Images by Data-Driven Regression and Classification

In this paper we propose a new fully-automatic method for localizing and segmenting 3D intervertebral discs from MR images, where the two problems are solved in a unified data-driven regression and classification framework. We estimate the output (image displacements for localization, or fg/bg labels for segmentation) of image points by exploiting both training data and geometric constraints simultaneously. The problem is formulated in a unified objective function which is then solved globally and efficiently. We validate our method on MR images of 25 patients. Taking manually labeled data as the ground truth, our method achieves a mean localization error of 1.3 mm, a mean Dice metric of 87%, and a mean surface distance of 1.3 mm. Our method can be applied to other localization and segmentation tasks.

Localization and Segmentation of 3D Intervertebral Discs in MR Images by Data Driven Estimation

This paper addresses the problem of fully-automatic localization and segmentation of 3D intervertebral discs (IVDs) from MR images. Our method contains two steps, where we first localize the center of each IVD, and then segment IVDs by classifying image pixels around each disc center as foreground (disc) or background. The disc localization is done by estimating the image displacements from a set of randomly sampled 3D image patches to the disc center. The image displacements are estimated by jointly optimizing the training and test displacement values in a data-driven way, where we take into consideration both the training data and the geometric constraint on the test image. After the disc centers are localized, we segment the discs by classifying image pixels around disc centers as background or foreground. The classification is done in a similar data-driven approach as we used for localization, but in this segmentation case we are aiming to estimate the foreground/background probability of each pixel instead of the image displacements. In addition, an extra neighborhood smooth constraint is introduced to enforce the local smoothness of the label field. Our method is validated on 3D T2-weighted turbo spin echo MR images of 35 patients from two different studies. Experiments show that compared to state of the art, our method achieves better or comparable results. Specifically, we achieve for localization a mean error of 1.6-2.0 mm, and for segmentation a mean Dice metric of 85%-88% and a mean surface distance of 1.3-1.4 mm.

Dish Detection and Segmentation for Dietary Assessment on Smartphones

Diet-related chronic diseases severely affect personal and global health. However, managing or treating these diseases currently requires long training and high personal involvement to succeed. Computer vision systems could assist with the assessment of diet by detecting and recognizing different foods and their portions in images. We propose novel methods for detecting a dish in an image and segmenting its contents with and without user interaction. All methods were evaluated on a database of over 1600 manually annotated images. The dish detection scored an average of 99% accuracy with a .2s/image run time, while the automatic and semi-automatic dish segmentation methods reached average accuracies of 88% and 91% respectively, with an average run time of .5s/image, outperforming competing solutions.