Automatic attention lateral asymmetry in visual discrimination tasks

There is evidence that automatic visual attention favors the right side. This study investigated whether this lateral asymmetry interacts with the right hemisphere dominance for visual location processing and left hemisphere dominance for visual shape processing. Volunteers were tested in a location discrimination task and a shape discrimination task. The target stimuli (S2) could occur in the left or right hemifield. They were preceded by an ipsilateral, contralateral or bilateral prime stimulus (S1). The attentional effect produced by the right S1 was larger than that produced by the left S1. This lateral asymmetry was similar between the two tasks suggesting that the hemispheric asymmetries of visual mechanisms do not contribute to it. The finding that it was basically due to a longer reaction time to the left S2 than to the right S2 for the contralateral S1 condition suggests that the inhibitory component of attention is laterally asymmetric.

Effets de privations sélectives en sommeil lent et en sommeil paradoxal sur l'attention automatique et sélective

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

Interlateral asymmetry in the time course of the effect of a peripheral prime stimulus

Evidence exists that both right and left hemisphere attentional mechanisms are mobilized when attention is directed to the right visual hemifield and only right hemisphere attentional mechanisms are mobilized when attention is directed to the left visual hemifield. This arrangement might lead to a rightward bias of automatic attention. The hypothesis was investigated by testing male volunteers, wherein a ""location discrimination"" reaction time task (Experiments 1 and 3) and a ""location and shape discrimination"" reaction time task (Experiments 2 and 4) were used. Unilateral (Experiments 1 and 2) and unilateral or bilateral (Experiments 3 and 4) peripheral visual prime stimuli were used to control attention. Reaction time to a small visual target stimulus in the same location or in the horizontally opposite location was evaluated. Stimulus onset asynchronies (SOAs) were 34, 50, 67, 83 and 100 ms. An important prime stimulus attentional effect was observed as early as 50 ms in the four experiments. In Experiments 2, 3 and 4, this effect was larger when the prime stimulus occurred in the right hemifield than when it occurred in the left hemifield for SOA 100 ms. In Experiment 4, when the prime stimulus occurred simultaneously in both hemifields, reaction time was faster for the right hemifield and for SOA 100 ms. These results indicate that automatic attention tends to favor the right side of space, particularly when identification of the target stimulus shape is required. (c) 2007 Elsevier Inc. All rights reserved.

Atenção automática para faces de compaixão no auto-criticismo

O auto-criticismo é um traço de personalidade preditor de psicopatologia. Sabe-se que indivíduos com elevado auto-criticismo tendem a processar a compaixão como um estímulo ameaçador. Apesar destes dados, a literatura é escassa no que se refere à forma como os indivíduos com elevado auto-criticismo reagem perante emoções complexas, como o criticismo e a compaixão. Desta forma, no presente estudo foram utilizadas faces de compaixão, criticismo e neutras como estímulos distratores, em que o estímulo relevante consistiu na identificação de uma letra num conjunto delas. Os resultados mostraram que as pessoas com elevado auto-criticismo tenderam a errar mais e a ter maiores tempos de resposta na tarefa principal quando o estímulo distrator foi uma face de compaixão. Estes dados sugerem que a atenção automática de indivíduos com elevado auto-criticismo pode ser afetada perante estímulos faciais de compaixão.

Automatic inference of driving task demand from visual cues of emotion and attention

Sensing the mental, physical and emotional demand of a driving task is of primary importance in road safety research and for effectively designing in-vehicle information systems (IVIS). Particularly, the need of cars capable of sensing and reacting to the emotional state of the driver has been repeatedly advocated in the literature. Algorithms and sensors to identify patterns of human behavior, such as gestures, speech, eye gaze and facial expression, are becoming available by using low cost hardware: This paper presents a new system which uses surrogate measures such as facial expression (emotion) and head pose and movements (intention) to infer task difficulty in a driving situation. 11 drivers were recruited and observed in a simulated driving task that involved several pre-programmed events aimed at eliciting emotive reactions, such as being stuck behind slower vehicles, intersections and roundabouts, and potentially dangerous situations. The resulting system, combining face expressions and head pose classification, is capable of recognizing dangerous events (such as crashes and near misses) and stressful situations (e.g. intersections and way giving) that occur during the simulated drive.

Automatic region-of-interest detection and prioritisation for visually optimised coding of low bit rate videos

The increasing popularity of video consumption from mobile devices requires an effective video coding strategy. To overcome diverse communication networks, video services often need to maintain sustainable quality when the available bandwidth is limited. One of the strategy for a visually-optimised video adaptation is by implementing a region-of-interest (ROI) based scalability, whereby important regions can be encoded at a higher quality while maintaining sufficient quality for the rest of the frame. The result is an improved perceived quality at the same bit rate as normal encoding, which is particularly obvious at the range of lower bit rate. However, because of the difficulties of predicting region-of-interest (ROI) accurately, there is a limited research and development of ROI-based video coding for general videos. In this paper, the phase spectrum quaternion of Fourier Transform (PQFT) method is adopted to determine the ROI. To improve the results of ROI detection, the saliency map from the PQFT is augmented with maps created from high level knowledge of factors that are known to attract human attention. Hence, maps that locate faces and emphasise the centre of the screen are used in combination with the saliency map to determine the ROI. The contribution of this paper lies on the automatic ROI detection technique for coding a low bit rate videos which include the ROI prioritisation technique to give different level of encoding qualities for multiple ROIs, and the evaluation of the proposed automatic ROI detection that is shown to have a close performance to human ROI, based on the eye fixation data.

Automatic surveillance in transportation hubs: No Longer just about catching the bad guy

As critical infrastructure such as transportation hubs continue to grow in complexity, greater importance is placed on monitoring these facilities to ensure their secure and efficient operation. In order to achieve these goals, technology continues to evolve in response to the needs of various infrastructure. To date, however, the focus of technology for surveillance has been primarily concerned with security, and little attention has been placed on assisting operations and monitoring performance in real-time. Consequently, solutions have emerged to provide real-time measurements of queues and crowding in spaces, but have been installed as system add-ons (rather than making better use of existing infrastructure), resulting in expensive infrastructure outlay for the owner/operator, and an overload of surveillance systems which in itself creates further complexity. Given many critical infrastructure already have camera networks installed, it is much more desirable to better utilise these networks to address operational monitoring as well as security needs. Recently, a growing number of approaches have been proposed to monitor operational aspects such as pedestrian throughput, crowd size and dwell times. In this paper, we explore how these techniques relate to and complement the more commonly seen security analytics, and demonstrate the value that can be added by operational analytics by demonstrating their performance on airport surveillance data. We explore how multiple analytics and systems can be combined to better leverage the large amount of data that is available, and we discuss the applicability and resulting benefits of the proposed framework for the ongoing operation of airports and airport networks.

Perception and Automatic Recognition of Laughter from Whole-Body Motion: Continuous and Categorical Perspectives

Despite its importance in social interactions, laughter remains little studied in affective computing. Intelligent virtual agents are often blind to users’ laughter and unable to produce convincing laughter themselves. Respiratory, auditory, and facial laughter signals have been investigated but laughter-related body movements have received less attention. The aim of this study is threefold. First, to probe human laughter perception by analyzing patterns of categorisations of natural laughter animated on a minimal avatar. Results reveal that a low dimensional space can describe perception of laughter “types”. Second, to investigate observers’ perception of laughter (hilarious, social, awkward, fake, and non-laughter) based on animated avatars generated from natural and acted motion-capture data. Significant differences in torso and limb movements are found between animations perceived as laughter and those perceived as non-laughter. Hilarious laughter also differs from social laughter. Different body movement features were indicative of laughter in sitting and standing avatar postures. Third, to investigate automatic recognition of laughter to the same level of certainty as observers’ perceptions. Results show recognition rates of the Random Forest model approach human rating levels. Classification comparisons and feature importance analyses indicate an improvement in recognition of social laughter when localized features and nonlinear models are used.

Alcohol attention bias in adolescent social drinkers: an eye tracking study

Rationale
Previous research on attention bias in nondependent social drinkers has focused on adult samples with limited focus on the presence of attention bias for alcohol cues in adolescent social drinkers.
Objectives
The aim of this study was to examine the presence of alcohol attention bias in adolescents and the relationship of this cognitive bias to alcohol use and alcohol-related expectancies.
Methods
Attention bias in adolescent social drinkers and abstainers was measured using an eye tracker during exposure to alcohol and neutral cues. Questionnaires measured alcohol use and explicit alcohol expectancies.
Results
Adolescent social drinkers spent significantly more time fixating to alcohol stimuli compared to controls. Total fixation time to alcohol stimuli varied in accordance with level of alcohol consumption and was significantly associated with more positive alcohol expectancies. No evidence for automatic orienting to alcohol stimuli was found in adolescent social drinkers.
Conclusion
Attention bias in adolescent social drinkers appears to be underpinned by controlled attention suggesting that whilst participants in this study displayed alcohol attention bias comparable to that reported in adult studies, the bias has not developed to the point of automaticity. Initial fixations appeared to be driven by alternative attentional processes which are discussed further.

Automatic Video Analysis for Fisheries Survey Systems

Thesis (Ph.D.)--University of Washington, 2015

Effects of divided attention and speeded responding on implicit and explicit retrieval of artificial grammar knowledge

The artificial grammar (AG) learning literature (see, e.g., Mathews et al., 1989; Reber, 1967) has relied heavily on a single measure of implicitly acquired knowledge. Recent work comparing this measure (string classification) with a more indirect measure in which participants make liking ratings of novel stimuli (e.g., Manza & Bornstein, 1995; Newell & Bright, 2001) has shown that string classification (which we argue can be thought of as an explicit, rather than an implicit, measure of memory) gives rise to more explicit knowledge of the grammatical structure in learning strings and is more resilient to changes in surface features and processing between encoding and retrieval. We report data from two experiments that extend these findings. In Experiment 1, we showed that a divided attention manipulation (at retrieval) interfered with explicit retrieval of AG knowledge but did not interfere with implicit retrieval. In Experiment 2, we showed that forcing participants to respond within a very tight deadline resulted in the same asymmetric interference pattern between the tasks. In both experiments, we also showed that the type of information being retrieved influenced whether interference was observed. The results are discussed in terms of the relatively automatic nature of implicit retrieval and also with respect to the differences between analytic and nonanalytic processing (Whittlesea Price, 2001).

Dissociating word stem completion and cued recall as a function of divided attention at retrieval

The aim of this study was to investigate the widely held, but largely untested, view that implicit memory (repetition priming) reflects an automatic form of retrieval. Specifically, in Experiment 1 we explored whether a secondary task (syllable monitoring), performed during retrieval, would disrupt performance on explicit (cued recall) and implicit (stem completion) memory tasks equally. Surprisingly, despite substantial memory and secondary costs to cued recall when performed with a syllable-monitoring task, the same manipulation had no effect on stem completion priming or on secondary task performance. In Experiment 2 we demonstrated that even when using a particularly demanding version of the stem completion task that incurred secondary task costs, the corresponding disruption to implicit memory performance was minimal. Collectively, the results are consistent with the view that implicit memory retrieval requires little or no processing capacity and is not seemingly susceptible to the effects of dividing attention at retrieval.

Psychophysics of emotion: the QUEST for emotional attention

To investigate the mechanisms involved in automatic processing of facial expressions, we used the QUEST procedure to measure the display durations needed to make a gender decision on emotional faces portraying fearful, happy, or neutral facial expressions. In line with predictions of appraisal theories of emotion, our results showed greater processing priority of emotional stimuli regardless of their valence. Whereas all experimental conditions led to an averaged threshold of about 50 ms, fearful and happy facial expressions led to significantly less variability in the responses than neutral faces. Results suggest that attention may have been automatically drawn by the emotion portrayed by face targets, yielding more informative perceptions and less variable responses. The temporal resolution of the perceptual system (expressed by the thresholds) and the processing priority of the stimuli (expressed by the variability in the responses) may influence subjective and objective measures of awareness, respectively.

Automatic ability attribution after failure: a dual process view of achievement attribution

Causal attribution has been one of the most influential frameworks in the literature of achievement motivation, but previous studies considered achievement attribution as relatively deliberate and effortful processes. In the current study, we tested the hypothesis that people automatically attribute their achievement failure to their ability, but reduce the ability attribution in a controlled manner. To address this hypothesis, we measured participants’ causal attribution belief for their task failure either under the cognitive load (load condition) or with full attention (no-load condition). Across two studies, participants attributed task performance to their ability more in the load than in the no-load condition. The increased ability attribution under cognitive load further affected intrinsic motivation. These results indicate that cognitive resources available after feedback play crucial roles in determining causal attribution belief, as well as achievement motivations. (PsycINFO Database Record (c) 2013 APA, all rights reserved)(journal abstract)

Aquatic weed automatic classification using machine learning techniques

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)