A robust steganography method for HEVC based on secret sharing

This paper presents a robust steganography method for HEVC based on secret sharing. To prevent intra-frame distortion drift, three Classes of intra-frame prediction are defined. To improve the robustness of the secret message, the embedded message has been encoded into n sub-secrets by using (t, n)-threshold secret sharing. Then the encoded message is embedded into the multi-coefficients of the selected 4 × 4 luminance DST blocks which meet the Classes mentioned above. When the test video faced with different loss-rates, the survival rate of the proposed steganography method has increased by around 24.27%, 27.38%, 61.91% and 32.26% compared with Swati, Hayat, and Shahid (2014), respectively; the survival rate of the proposed steganography method has increased by around 28.74%, 34.60%, 56.05% and 41.40% compared with Liu, Liu, and Zhao (2017), respectively; when the loss-rate is less than 15%, the proposed steganography method can get 100% survival rate. And the experiments prove that the proposed method can achieve high performance than previously video steganography methods based on HEVC, especially for visual quality and robustness performance.     

An illumination robust road detection method based on color names and geometric information

Road detection is a basic task in automated driving field. In existing methods, detecting lane marks is a frequently used approach. However, road marks could fade with time, or even do not exist on some roads. Considering these factors, road region segmentation from background is much more reliable. One of the difficulties in this area is dealing with variant illumination conditions. Existing methods make some progress on reducing the influence of shadows, but they are still not satisfactory. Taking this into account, we put forward an improved shadow-free road detecting method based on color names, whose performance exceeds the existing methods. In addition, to further improving our performance on application, we adopt vanishing point detection and fuse two confidence maps to reduce the interference of sidewalk regions. Experiments on KITTI dataset depict that the proposed method is efficient. Moreover, the improved road detection method has low-complexity, which meets the requirement of practical usage.     

A simple cell model with dominating opponent inhibition for robust contrast detection

Ein Modell kortikaler Einfachzellen mit dominanter opponenter Inhibition zur robusten Kontrastdetektion Zusammenfassung. Im primären visuellen Pfad wird Information in zwei getrennten, komplementären Domänen repräsentiert, den on- und off-Zellen. In dieser Arbeit untersuchen wir die Interaktion von on- und off-Zellen zur Generierung der Eingabe für eine kortikale Einfachzelle. Basierend auf physiologischen Studien schlagen wir einen Mechanismus vor, bei dem eine kortikale Einfachzelle aus beiden Domänen eine Eingabe erhält, wobei die Eingabe aus dem opponenten Pfad stärker gewichtet wird. Mit diesem Mechanismus der dominanten opponenten Inhibition können Antworten von kortikalen Einfachzellen auf Hell-Dunkel-Balken simuliert werden, die im primären visuellen Kortex der Katze gemessen wurden. Bei der Verarbeitung synthetischer und natürlicher Bilder können mit dem neuen Modell schärfere Antworten und bessere Rauschunterdrückung erreicht werden. Wir geben eine stochastische Analyse der Rauschunterdrückungscharakteristika des vorgeschlagenen Mechanismus und präsentieren detaillierte numerische Simulationen mit systematischen Parametervariationen. Die Resultate zeigen, dass das Modell kortikaler Einfachzellen mit dominanter opponenter Inhibition robuster gegenüber verrauschten Eingaben wird, weitgehend unabhängig von der Stärke des Rauschens. Diese Eigenschaft ist möglicherweise der Grund für die physiologisch gemessene dominante Inhibition und für die Repräsentation von Kontrastinformation in zwei komplementären Domänen. Basierend auf diesen Ergebnissen stellen wir die Hypothese auf, dass dominante opponente Inhibition im visuellen System verwendet wird, um in verrauschten Umgebungen Kontraste robust extrahieren zu können. Summary. In the primary visual pathway, information is represented in two distinct, complementary domains, namely "on" and "off" cells. In this work we examine how on and off cells may interact to form the input to simple cell subfields. On the basis of physiological evidence, we propose a mechanism of dominating opponent inhibition, where a simple cell subfield is driven by both on and off domains, receiving more heavily weighted input from the opponent pathway. We demonstrate that the model can account for physiological data on luminance gradient reversal recorded from simple cells in cat striate cortex. Next, we use the model for the processing of synthetic and natural images, showing that sharpness of response and robustness to noise can be increased by dominating opponent inhibition. Finally, we present a stochastic analysis of the noise-suppression characteristics of the proposed mechanism accompanied by detailed simulations with systematic parameter variations. Results show that dominating opponent inhibition makes the simple cell responses more robust to noise, largely independently of the amount of noise added. This property may give a rationale for the strong inhibition measured physiologically and for the representation of contrast information in two complementary domains. On the basis of these findings, we hypothesize that the visual system uses dominating opponent inhibition in order to robustly extract features in noisy environments.     

A robust method for the analysis of experiments with ordered treatment levels.

A robust approach for the analysis of experiments with ordered treatment levels is presented as an alternative to existing approaches such as the parametric Abelson-Tukey test for monotone alternatives and the nonparametric Terpstra-Jonckheere test. The method integrates the familiar Spearman rank-order correlation with bootstrap routines to provide magnitude of association measures, p values, and confidence intervals for magnitude of association measures. The advantages of this method relative to five alternative approaches are pointed out.     

A comparison of sniff bottle staircase and olfactometer-based threshold tests

Olfactometers have been gaining popularity as research tools, but they have yet to replace established testing procedures in a variety of laboratory and clinical settings, including absolute threshold tests. In this research, we designed and operated a simple olfactometer with which to assess threshold. To do this, we used a method-of-adjustment test that was compared to the three-alternative forced choice ascending sniff bottle staircase method, which is currently a standard threshold test procedure. We found that the olfactometer threshold test correlated highly with the staircase method, and that it possessed suitable test–retest reliability. The advantages of the olfactometer threshold test include faster test time and reduced cleaning and reassembly demands. Future use of the olfactometer in olfactory identification and/or detection thresholds amongst odors is also outlined.     

Signal detection and localization by real observers

A model for detection and localization (DAL) was applied to the processing of a noise-masked tonal signal by human Ss. The model was supported in that consistent values of d’ were obtained from rating. forced-choice (FC). and DAL procedures. Also. the rating d’ accurately predicted per cent correct on the FC and DAL trials. A shortcoming of the theory was its failure to account satisfactorily for the details of FC and DAL stimulus-response matrices.     

A simple method for latency analysis in signal detection tasks

It proved that the difference between mean latency for incorrect responses and mean latency for correct ones in signal detection situations can be used as a measure for the separation between SN and N distributions, provided that certain plausible conditions are met. The applicability of this method to various paradigms is briefly discussed.     

A robust classic

In the present research, we argue for the robustness of illusory correlations (ICs, Hamilton & Gifford, 1976) regarding two boundary conditions suggested in previous research. First, we argue that ICs are maintained under extended experience. Using simulations, we derive conflicting predictions. Whereas noise-based accounts predict ICs to be maintained (Fielder, 2000; Smith, 1991), a prominent account based on discrepancy-reducing feedback learning predicts ICs to disappear (Van Rooy et al., 2003). An experiment involving 320 observations with majority and minority members supports the claim that ICs are maintained. Second, we show that actively using the stereotype to make predictions that are met with reward and punishment does not eliminate the bias. In addition, participants' operant reactions afford a novel online measure of ICs. In sum, our findings highlight the robustness of ICs that can be explained as a result of unbiased but noisy learning.     

Visual facilitation of auditory localization in schoolchildren: A signal detection analysis

Warren (1970) has claimed that there are visual facilitation effects on auditory localization in adults but not in children. He suggests that a “visual map” organizes spatial information and that considerable experience of correlated auditory and visual events is necessary before normal spatial perception is developed. In the present experiment, children in Grades 1, 4, and 7 had to identify the position, right or left, of a single tone either blindfolded or with their eyes open. Analysis of the proportion of area under the ROC curve (obtained using reaction times) in the respective conditions showed that Ss were more sensitive to auditory position when vision was available. Reaction time was also generally faster in the light. I argue that the increase in sensitivity in the light represents updating of auditory position memory by voluntary eye movement. In the dark, eye movements are subject to involuntary and unperceived drift, which would introduce noise into the eye control mechanism and hence into auditory spatial memory.     

Testing for negligible interaction: A coherent and robust approach

Researchers often want to demonstrate a lack of interaction between two categorical predictors on an outcome. To justify a lack of interaction, researchers typically accept the null hypothesis of no interaction from a conventional analysis of variance (ANOVA). This method is inappropriate as failure to reject the null hypothesis does not provide statistical evidence to support a lack of interaction. This study proposes a bootstrap‐based intersection–union test for negligible interaction that provides coherent decisions between the omnibus test and post hoc interaction contrast tests and is robust to violations of the normality and variance homogeneity assumptions. Further, a multiple comparison strategy for testing interaction contrasts following a non‐significant omnibus test is proposed. Our simulation study compared the Type I error control, omnibus power and per‐contrast power of the proposed approach to the non‐centrality‐based negligible interaction test of Cheng and Shao (2007, Statistica Sinica, 17, 1441). For 2 × 2 designs, the empirical Type I error rates of the Cheng and Shao test were very close to the nominal α level when the normality and variance homogeneity assumptions were satisfied; however, only our proposed bootstrapping approach was satisfactory under non‐normality and/or variance heterogeneity. In general a × b designs, although the omnibus Cheng and Shao test, as expected, is the most powerful, it is not robust to assumption violation and results in incoherent omnibus and interaction contrast decisions that are not possible with the intersection–union approach.     

Visual search: detection, identification, and localization.

In two studies, observers searched for a single oblique target in a field of vertical distractors. In one experiment, target detection and identification (left versus right tilt) were compared. In another experiment, detection and localization were compared for the left versus the right half of the display. Performance on all three tasks was virtually identical: if a target could be detected, it could also be identified and localized. A review of previous studies generally supports the conclusion that performance on the three tasks is similar. This argues against current search theories, which rest heavily on data showing differences in identification and localization.     

Developmental perspectives on the localization and detection of auditory signals

Responsiveness of 1-, 3-, and 5-year-old children and adults to octave-band noises at .4 and 10 kHz was assessed with a go/no-go version of visual reinforcement audiometry (VRA) (Moore, Thompson, & Thompson, 1975) and a two-alternative, forced-choice version (Suzuki & Ogiba, 1961; Trehub, Schneider, & Endman, 1980). Infants performed better on the two-alternative, forced-choice version in quiet and in noisy backgrounds, and adults performed better on the two-alternative, forced-choice version in quiet but not in noisy backgrounds. Performance on the two tasks was essentially equivalent for 3- and 5-year-old children. Superior performance on two-alternative VRA over go/no-go may be due to lesser cognitive demands in the case of infants and to the engagement of superior decision strategies in the case of adults.     

Word cues affect detection but not localization responses

Many theories assume that preknowledge of an upcoming target helps visual selection. In those theories, a top-down set can alter the salience of the target, such that attention can be deployed to the target more efficiently and responses are faster. Evidence for this account stems from visual search studies in which the identity of the upcoming target is cued in advance. In five experiments, we show that top-down knowledge affects the speed with which a singleton target can be detected but not the speed with which it can be localized. Furthermore, we show that these results are independent of the mode of responding (manual or saccadic) and are not due to a ceiling effect. Our results suggest that in singleton search, top-down information does not affect visual selection but most likely does affect response selection. We argue that such an effect is found only when information from different dimensions needs to be integrated to generate a response and that this is the case in singleton detection tasks but not in other singleton search tasks.     

A novel blink detection method based on pupillometry noise

Pupillometry (or the measurement of pupil size) is commonly used as an index of cognitive load and arousal. Pupil size data are recorded using eyetracking devices that provide an output containing pupil size at various points in time. During blinks the eyetracking device loses track of the pupil, resulting in missing values in the output file. The missing-sample time window is preceded and followed by a sharp change in the recorded pupil size, due to the opening and closing of the eyelids. This eyelid signal can create artificial effects if it is not removed from the data. Thus, accurate detection of the onset and the offset of blinks is necessary for pupil size analysis. Although there are several approaches to detecting and removing blinks from the data, most of these approaches do not remove the eyelid signal or can result in a relatively large amount of data loss. The present work suggests a novel blink detection algorithm based on the fluctuations that characterize pupil data. These fluctuations (“noise”) result from measurement error produced by the eyetracker device. Our algorithm finds the onset and offset of the blinks on the basis of this fluctuation pattern and its distinctiveness from the eyelid signal. By comparing our algorithm to three other common blink detection methods and to results from two independent human raters, we demonstrate the effectiveness of our algorithm in detecting blink onset and offset. The algorithm’s code and example files for processing multiple eye blinks are freely available for download (https://osf.io/jyz43).     

A generally robust approach for testing hypotheses and setting confidence intervals for effect sizes

Standard least squares analysis of variance methods suffer from poor power under arbitrarily small departures from normality and fail to control the probability of a Type I error when standard assumptions are violated. This article describes a framework for robust estimation and testing that uses trimmed means with an approximate degrees of freedom heteroscedastic statistic for independent and correlated groups designs in order to achieve robustness to the biasing effects of nonnormality and variance heterogeneity. The authors describe a nonparametric bootstrap methodology that can provide improved Type I error control. In addition, the authors indicate how researchers can set robust confidence intervals around a robust effect size parameter estimate. In an online supplement, the authors use several examples to illustrate the application of an SAS program to implement these statistical methods.     

A neurophysiological explanation for biases in visual localization

Observers show small but systematic deviations from equal weighting of all elements when asked to localize the center of an array of dots. Counter-intuitively, with small numbers of dots drawn from a Gaussian distribution, this bias results in subjects overweighting the influence of outlier dots – inconsistent with traditional statistical estimators of central tendency. Here we show that this apparent statistical anomaly can be explained by the observation that outlier dots also lie in regions of lower dot density. Using a standard model of V1 processing, which includes spatial integration followed by a compressive static nonlinearity, we can successfully predict the finding that dots in less dense regions of an array have a relatively greater influence on the perceived center.