Luminance Change Detection Research Articles

Separate contributions of autistic traits and anxious apprehension, but not alexithymia, to emotion processing in faces.

Reduced eye fixation has been commonly reported in autistic samples but may be at least partially explained by alexithymia (i.e., difficulty understanding and describing one's emotional state). Because anxiety is often elevated in autism, and emotion-processing differences have also been observed in anxious samples, anxiety traits may also influence emotion processing within autism. This study tested the contribution of dimensional traits of autism, anxious apprehension, and alexithymia in mediating eye fixation during face processing. Participants included 105 adults from three samples: autistic adults (AS; n = 30), adults with clinically elevated anxiety and no autism (HI-ANX; n = 29), and neurotypical adults without elevated anxiety (NT; n = 46). Experiment 1 used an emotion identification task with dynamic stimuli, while Experiment 2 used a static luminance change detection task with emotional- and neutral-expression static photos. The emotions of interest were joy, anger, and fear. Dimensional mixed-effects models showed that autism traits, but not alexithymia, predicted reduced eye fixation across both tasks. Anxious apprehension was negatively related to response time in Experiment 1 and positively related to eye fixation in Experiment 2. Attentional avoidance of negative stimuli occurred at lower levels of autism traits and higher levels of worry traits. The results highlight the contribution of autism traits to emotional processing and suggest additional effects of worry-related traits.

On event-based optical flow detection.

Event-based sensing, i.e., the asynchronous detection of luminance changes, promises low-energy, high dynamic range, and sparse sensing. This stands in contrast to whole image frame-wise acquisition by standard cameras. Here, we systematically investigate the implications of event-based sensing in the context of visual motion, or flow, estimation. Starting from a common theoretical foundation, we discuss different principal approaches for optical flow detection ranging from gradient-based methods over plane-fitting to filter based methods and identify strengths and weaknesses of each class. Gradient-based methods for local motion integration are shown to suffer from the sparse encoding in address-event representations (AER). Approaches exploiting the local plane like structure of the event cloud, on the other hand, are shown to be well suited. Within this class, filter based approaches are shown to define a proper detection scheme which can also deal with the problem of representing multiple motions at a single location (motion transparency). A novel biologically inspired efficient motion detector is proposed, analyzed and experimentally validated. Furthermore, a stage of surround normalization is incorporated. Together with the filtering this defines a canonical circuit for motion feature detection. The theoretical analysis shows that such an integrated circuit reduces motion ambiguity in addition to decorrelating the representation of motion related activations.

A background model re-initialization method based on sudden luminance change detection

Sudden changes in illumination often occur in real world scenarios and may cause considerable difficulties in modeling backgrounds for the state-of-the-art background subtraction methods. In this paper, we propose a simple and effective background re-initialization method that detects sudden luminance change effectively. The purpose of the proposed method is not on the presentation of a specific solution for object detection, but is instead the improvement of the background subtraction approach so that it is capable of sudden luminance change adaptation. Two embodiments related to background subtraction, and which are based on the proposed method, are also presented. These embodiments can detect the moving objects accurately as the luminance of the background model is adjusted quickly after the proposed method is employed for generating the background model. Experimental results demonstrate that the proposed method effectively improves the background subtraction methods as measured by qualitative as well as quantitative assessments.

Distribution of Attention in Augmented Reality: Comparison between Binocular and Monocular Presentation

SUMMARY This study investigated the distribution of attention to frontal space in augmented reality (AR). We conducted two experiments to compare binocular and monocular observation when an AR image was presented. According to a previous study, when participants observed an AR image in monocular presentation, they perceived the AR image as more distant than in binocular vision. Therefore, we predicted that attention would need to be shifted between the AR image and the background in not the monocular observation but the binocular one. This would enable an observer to distribute his/ her visual attention across a wider space in the monocular observation. In the experiments, participants performed two tasks concurrently to measure the size of the useful field of view (UFOV). One task was letter/ number discrimination in which an AR image was presented in the central field of view (the central task). The other task was luminance change detection in which dots were presented in the peripheral field of view (the peripheral task). Depth difference existed between the AR image and the location of the peripheral task in Experiment 1 but not in Experiment 2. The results of Experiment 1 indicated that the UFOV became wider in the monocular observation than in the binocular observation. In Experiment 2, the size of the UFOV in the monocular observation was equivalent to that in the binocular observation. It becomes difficult for a participant to observe the stimuli on the background in the binocular observation when there is depth difference between the AR image and the background. These results indicate that the monocular presentation in AR is superior to binocular presentation, and even in the best condition for the binocular condition the monocular presentation is equivalent to the binocular presentation in terms of the UFOV.

Isoluminant motion onset captures attention

In their 2003 article, Abrams and Christ found that the onset of motion captured attention more effectively than either the offset of motion or continuous motion. Abrams and Christ conceptualized the capture to be occurring at a level higher than does detection of luminance changes in the stimulus. To examine this claim, in the present experiments we replicated their critical experiment but used isoluminant stimuli, which do not produce the low-level luminance transients typically associated with motion. Under isoluminant conditions, we found a pattern of results very similar to that found previously with luminance-defined stimuli, indicating that attention can be prioritized on the basis of perceived motion onset by an object in the absence of low-level luminance transients. This may reflect an evolutionary adaptation to bias attention toward objects that exhibit characteristics of animacy, such as abruptly changing from a static to a dynamic state.

Normal Spatial Attention But Impaired Saccades and Visual Motion Perception After Lesions of the Monkey Cerebellum

Lesions of the cerebellum produce deficits in movement and motor learning. Saccadic dysmetria, for example, is caused by lesions of the posterior cerebellar vermis. Monkeys and patients with such lesions are unable to modify the amplitude of saccades. Some have suggested that the effects on eye movements might reflect a more global cognitive deficit caused by the cerebellar lesion. We tested that idea by studying the effects of vermis lesions on attention as well as saccadic eye movements, visual motion perception, and luminance change detection. Lesions in posterior vermis of four monkeys caused the known deficits in saccadic control. Attention tested by examination of acuity threshold changes induced by prior cueing of the location of the targets remained normal after vermis lesions. Luminance change detection was also unaffected by the lesions. In one case, after a lesion restricted to lobulus VIII, the animal had impaired visual motion perception.

Audiovisual integration of stimulus transients

A change in sound intensity can facilitate luminance change detection. We found that this effect did not depend on whether sound intensity and luminance increased or decreased. In contrast, luminance identification was strongly influenced by the congruence of luminance and sound intensity change leaving only unsigned stimulus transients as the basis for audiovisual integration. Facilitation of luminance detection occurred even with varying audiovisual stimulus onset asynchrony and even when the sound lagged behind the luminance change by 75 ms supporting the interpretation that perceptual integration rather than a reduction of temporal uncertainty or effects of attention caused the effect.

Change perception using visual transients: object substitution and deletion

In three experiments we studied change detection and identification when no extraneous transients were present in the image at the time of change. Each image consisted of 12 different objects, sorted by color into three different levels of probability of change. In Experiment 1, change of one object was detected and identified frequently in objects having the highest probability of change (central interest), which we hypothesize were mainly visited by attention. Changes in other objects with a lower probability of change (marginal interest), however, although detected efficiently were unlikely to be identified. Identification improved for less attended objects if the changed stimulus simply disappeared, allowing visual persistence to hold information about the object until attention could be shifted to it (Experiment 2). Contrary to previous findings showing that response times (RTs) for luminance change detection in a multi-element display are not altered by attention, we found changes in objects of central interest to be detected faster than in objects of marginal interest when objects' identity was to be held in working memory. However, no differences in RTs emerged in the same change detection task when objects' identity was not stored in working memory (Experiment 3).

Do equiluminant object onsets capture visual attention?

S. Yantis and A. P. Hillstrom (1994) have claimed that abrupt onset of a new visual object captures attention even when the new object is equiluminant with its background, implying that attention is captured at the level of object descriptions rather than at the level of luminance change detection. S. Yantis and A. P. Hillstrom's experiments contained potential flaws that call their conclusion into question. The present article reports 5 experiments investigating these and related issues. The results suggest that for abruptly onsetting visual objects to capture attention, detection of change in a dimension of sensory stimulation is a necessary, but perhaps not a sufficient, requirement. Evidence is also presented against the view that attentional priority for new objects arises as a result of visual masking of old objects in the same displays.

The Role of Attention in the Detection of Luminance Changes: Endogenous versus Exogenous Cueing

Many visual tasks have been shown to be influenced by the attentional state of the observer. However the conditions under which attention has effects is still unclear. Here we report upon a series of experiments where the observer has to react to changes in the luminance of a target amongst many distractors. We have systematically manipulated the nature of the cue (endogenous vs exogenous) and the task to be performed (detection of changes vs discrimination of direction of change). Stimuli consisted of a number of circles upon a screen. At some point in time one of the circles changed in luminance and subjects reacted as quickly as possible. Typically half the circles were red and half green. Subjects could be cued to attend to a particular colour by instruction (endogenous) or by a brief flash of the lines that joined the same coloured elements (exogenous). In most cases the cue was appropriate on 80% of the trials and hence we could compare response times between valid and invalid trials. Our results show that (1) for simple detection endogenous cues were ineffective whereas exogenous cues provided a small advantage for the valid trials, and (2) for discrimination of direction of change endogenous cues provided a small advantage, whereas exogenous cues provided a large advantage for the valid trials. It appears that both cueing type and task type modulate the attentional effects on this ‘preattentive’ task.

Stimulus-driven attentional capture: evidence from equiluminant visual objects.

Previous work has shown that abrupt visual onsets capture attention. Possible attention. Possible mechanisms for this phenomenon include (a) a luminance-change detection system and (b) a mechanism that detects the appearance of new perceptual objects. Experiments 1 and 2 revealed that attention is captured in visual search by the appearance of a new perceptual object even when the object is equiluminant with its background and thus exhibits no luminance change when it appears. Experiment 3 showed that a highly salient luminance increment alone is not sufficient to capture attention. These findings suggest that attentional capture is mediated by a mechanism that detects the appearance of new perceptual objects.

Site of the accelerating nonlinearity underlying luminance-change detection.

The visual psychometric function for luminance-increment detectability (d') is known to be an accelerating function of stimulus energy. Two different models have been suggested to explain this fact and also why a luminance-increment pedestal linearizes the psychometric function. In the present experiment it is shown that a dichoptically presented increment linearizes the psychometric function and facilitates detection of weak signals. Since the dichoptic pedestal combines with the signal centrally, the nonlinearity must then originate more centrally. This result is compatible with the uncertainty model of the nonlinear psychometric function but not with a model that requires a nonlinear transducer.