On the Distribution of Salient Objects in Web Images and its Influence on Salient Object Detection

It has become apparent that a Gaussian center bias can serve as an important prior for visual saliency detection, which has been demonstrated for predicting human eye fixations and salient object detection. Tseng et al. have shown that the photographer's tendency to place interesting objects in the center is a likely cause for the center bias of eye fixations. We investigate the influence of the photographer's center bias on salient object detection, extending our previous work. We show that the centroid locations of salient objects in photographs of Achanta and Liu's data set in fact correlate strongly with a Gaussian model. This is an important insight, because it provides an empirical motivation and justification for the integration of such a center bias in salient object detection algorithms and helps to understand why Gaussian models are so effective. To assess the influence of the center bias on salient object detection, we integrate an explicit Gaussian center bias model into two state-of-the-art salient object detection algorithms. This way, first, we quantify the influence of the Gaussian center bias on pixel- and segment-based salient object detection. Second, we improve the performance in terms of F1 score, Fb score, area under the recall-precision curve, area under the receiver operating characteristic curve, and hit-rate on the well-known data set by Achanta and Liu. Third, by debiasing Cheng et al.'s region contrast model, we exemplarily demonstrate that implicit center biases are partially responsible for the outstanding performance of state-of-the-art algorithms. Last but not least, as a result of debiasing Cheng et al.'s algorithm, we introduce a non-biased salient object detection method, which is of interest for applications in which the image data is not likely to have a photographer's center bias (e.g., image data of surveillance cameras or autonomous robots)

SPLINE MODELS FOR ESTIMATING HEAT STRESS THRESHOLDS IN CATTLE

Studies of the relationship between animal body temperature and air temperature suggest body temperature is essentially unresponsive until a threshold is reached, then it responds dramatically to increasing air temperature. The goal is to estimate the threshold between the thermoneutral plateau and the beginning of the heat stress challenge. One approach is to fit a polynomial to estimate the knot position and use spline functions to perform linear least squares piecewise polynomial fitting. Another alternative is to use nonlinear regression to estimate the knot or an inflection point of a nonlinear function. In both approaches the cyclic nature of body temperature is ignored. This paper explores the use of nonlinear regression to estimate the knot position and handles the hysteresis effect resulting from the cyclic nature of body temperature. Models are fit to data collected from cattle in chambers subjected to semicontrolled sinusoidal air temperature at the University of Missouri-Columbia Animal Science department and a procedure for estimating the heat stress threshold is proposed

USING NONLINEAR FIXED AND MIXED MODELS TO STUDY ACCLIMATION TO HEAT STRESS IN CATTLE

Researchers studying acclimation of cattle to heat stress want to know if exposure to heat stress in controlled chambers will help cattle adjust to climatic conditions in the field. The four parameter nonlinear PET model is used to study the relationship between core body temperature and ambient temperature. This model works well when cattle are challenged by heat stress but the model is less useful for thermoneutral conditions. Both proc Nlin and Nlmixed are used to compare and contrast the field parameters between the controlled and the potentially acclimated group. Simulation studies were used to compare the effectiveness of proc Nlin versus proc Nlmixed. The results are helpful, not only for researchers who study acclimation, but also for those who study sensitivity, tolerance and robustness of cattle during heat stress

Multiscale Discriminant Saliency for Visual Attention

The bottom-up saliency, an early stage of humans' visual attention, can be considered as a binary classification problem between center and surround classes. Discriminant power of features for the classification is measured as mutual information between features and two classes distribution. The estimated discrepancy of two feature classes very much depends on considered scale levels; then, multi-scale structure and discriminant power are integrated by employing discrete wavelet features and Hidden markov tree (HMT). With wavelet coefficients and Hidden Markov Tree parameters, quad-tree like label structures are constructed and utilized in maximum a posterior probability (MAP) of hidden class variables at corresponding dyadic sub-squares. Then, saliency value for each dyadic square at each scale level is computed with discriminant power principle and the MAP. Finally, across multiple scales is integrated the final saliency map by an information maximization rule. Both standard quantitative tools such as NSS, LCC, AUC and qualitative assessments are used for evaluating the proposed multiscale discriminant saliency method (MDIS) against the well-know information-based saliency method AIM on its Bruce Database wity eye-tracking data. Simulation results are presented and analyzed to verify the validity of MDIS as well as point out its disadvantages for further research direction.Comment: 16 pages, ICCSA 2013 - BIOCA sessio

CHARACTERIZING THERMAL HYSTERESIS IN BODY TEMPERATURE FOR A HEAT STRESSED STEER

Studies have shown that exposure of animals to a high ambient temperature environment poses serious threats to their health, performance and productivity. Above a certain threshold an animal\u27s body temperature (Tb) appears to be driven by the hot ambient temperature (Ta). For steers challenged by heat stress, the Tb-Ta relationship shows a dramatic increase in Tb per unit change of Ta and the dynamics of the Tb-Ta relationship follow a pattern which depends on whether Ta is increasing or decreasing. A delay becomes noticeable in a steer’s thermo-regulatory response to Ta when Ta is controlled to be sinusoidal in the steer’s heat stress chamber. In other words, Tb lags behind Ta. Consequently when plotted in a Tb-Ta phase diagram, a hysteresis effect appears in the form of a hysteresis loop, indicating the steer is thermally challenged. The hysteresis loop shows a rotated elliptical pattern which depends on the delay (or lag) between Tb and Ta. The angle of rotation of the hysteresis loop indicates the correlation (and lag) between Tb and Ta. The area of the elliptical hysteresis loop can be used to quantify the amount of heat stress during the period of thermal challenge. For example, results of a thermal challenge of 32±7oC applied to a Hereford steer showed, the delay is longer (4 hr lag) and ellipse is larger in an acute stage than in a chronic stage (3 hr lag). A greater delay (or lag) suggests more time is needed to dissipate the heat stress. This result suggests, steers in an acute stage require more energy to dissipate heat than steers in a chronic stage

COMPARING CORRELATED PARAMETER ESTIMATES FOR NONLINEAR PET MODEL

The nonlinear PET model based on Newton\u27s law of cooling can be used to estimate body temperature in cattle, T b challenged by hot cyclic chamber temperatures, T a . The PET model has four biologically meaningful parameters: K, the thermal constant; Δ, the difference between T b and adjusted T a ; Υ the proportion of variation in T b comparable to variation in Ta ; T bini, the initial body temperature. The two parameters Y and Δ are highly correlated in the current version of the model. This study looks at other ways to parameterize the PET model in an effort to reduce the correlation between parameters and improve nonlinear behaviors, such as parameter-effects curvature, bias, excess variance and skewness

Role of CaCO3° neutral pair in calcium carbonate crystallization

The molecular structure of the units that get incorporated into the nuclei of the crystalline phase and sustain their growth is a fundamental issue in the pathway from a supersaturated solution to the formation of crystals. Using a fluorescent dye we have recorded the variation of the pH value in time along a gel where CaCl2 and NaHCO3 counter-diffuse to crystallize CaCO3. The same pH–space–time distribution maps were also computationally obtained using a chemical speciation code (phreeqc). Using data arising from this model we investigated the space-time evolution of the activity of the single species (ions and ion pairs) involved in the crystallization process. Our combined results suggest that, whatever the pathway from solution to crystals, the neutral pair CaCO3° is a key species in the CaCO3 precipitation system.European Research Council (European Union’s Seventh Framework Programme (FP7/2007-2013) grant agreement no 340863, and Spanish MINECO grants MAT2014-60533-R and CGL2010-16882 cofounded with FEDERPeer reviewe

Damaging real lives through obstinacy: re-emphasising why significance testing is wrong

This paper reminds readers of the absurdity of statistical significance testing, despite its continued widespread use as a supposed method for analysing numeric data. There have been complaints about the poor quality of research employing significance tests for a hundred years, and repeated calls for researchers to stop using and reporting them. There have even been attempted bans. Many thousands of papers have now been written, in all areas of research, explaining why significance tests do not work. There are too many for all to be cited here. This paper summarises the logical problems as described in over 100 of these prior pieces. It then presents a series of demonstrations showing that significance tests do not work in practice. In fact, they are more likely to produce the wrong answer than a right one. The confused use of significance testing has practical and damaging consequences for people's lives. Ending the use of significance tests is a pressing ethical issue for research. Anyone knowing the problems, as described over one hundred years, who continues to teach, use or publish significance tests is acting unethically, and knowingly risking the damage that ensues

Visual saliency and semantic incongruency influence eye movements when inspecting pictures

Models of low-level saliency predict that when we first look at a photograph our first few eye movements should be made towards visually conspicuous objects. Two experiments investigated this prediction by recording eye fixations while viewers inspected pictures of room interiors that contained objects with known saliency characteristics. Highly salient objects did attract fixations earlier than less conspicuous objects, but only in a task requiring general encoding of the whole picture. When participants were required to detect the presence of a small target, then the visual saliency of nontarget objects did not influence fixations. These results support modifications of the model that take the cognitive override of saliency into account by allowing task demands to reduce the saliency weights of task-irrelevant objects. The pictures sometimes contained incongruent objects that were taken from other rooms. These objects were used to test the hypothesis that previous reports of the early fixation of congruent objects have not been consistent because the effect depends upon the visual conspicuity of the incongruent object. There was an effect of incongruency in both experiments, with earlier fixation of objects that violated the gist of the scene, but the effect was only apparent for inconspicuous objects, which argues against the hypothesis