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Psychology: Behavioural Science

Table of Contents

Abstract

Introduction.

Discussion.

References.

Abstract on Visual Crowding Lab Report

Visual crowding could be understood as the failure in recognizing the objects in chaos, this set up an elementary limit on cognizant insight and recognition of the object throughout most of the visual field. It becomes quite difficult to notice the changes that have been occurring in even an apparent view of an observer. This could happen in a movement of eye blink or any other distraction. This study was done to observe the visual crowding and to analyse the changes observed among the 393 subjects that participated to observe two sets of pre-recorded movies. The experiment was done in trials. Average body categorisation performance was measured in the target alone as well as in the crowded experimental conditions. After 80 trials, the experiment movie was finished and the results were observed.

Introduction to Visual Crowding Lab Report

An individual’s ability to recognize objects has been seen to be restricted in clutter, chiefly in tangential vision. Representation of such visual crowding has been facilitated usually by the phenomenological misidentifications of the visually crowded targets. This has been done by using pairs of stimuli that generally do not merge to form an exclusive symbol or object. Spectators typically used to confuse the object source and this results from them in reporting for either the target or the distracter, but when incessant features are being used the spectators generally report a feature that lies somewhere between the distracter and the target (Harrison & Bex, 2017).

This laboratory report is based on “visual crowding”. Till now, the impact has been produced and seen by altering the images that have been displayed on the screen. And, the change in the other objects has also been made in a particular environment to view the change (Attwood et al., 2018). Crowding has been considered as an essential bottleneck. And, the setting has few limits that depend on the eye blinks, object perception, visual search, hand movements, reading and possibly all the other functions in the amblyopic, peripheral, and the developing vision. Crowding has been seen to prejudice not only bigotry of the features and contours of the object but also the capability to identify as well as respond suitably to the objects that have been present in the clutter. Therefore, learning visual crowding may often result in a better considerate of the processes that have been indulged in the identification of an object. Visual crowding also has certain significant clinical implications for the individuals that have been suffering from amblyopia, macular degeneration, and dyslexia (Whitney & Levi, 2011). Visual crowded objects do not generally disappear. And, it has also been stated in the study of Levi, (2008) that crowding alters the manifestation of the crowded region. This has been considered to be important because it could potentially help in distinguishing the main models for crowding. The main models of crowding encompass of masking, substitution, and pooling (Levi, 2008). In a study by Levi, (2008) it has been seen that on crowding unreservedly is a unitary occurrence, that occurs at a single restricted level regarding the visual processing, or conceivably in a specific visual area. Within each class, there have been various architectures as well as algorithms that have been proposed regarding this till now. Processing of the shape information in the field of human peripheral visuals has been obstructed further than what could be expected by the deprived spatial resolution. Visual crowding i.e., the failure to recognize the objects in clutter, has been considered to be the fundamental factor that limits the shape perception in the peripheral vision. . For experimenting the visual crowding and to scrutinize the relative differences either photographs or videos that have natural sights are used to be displayed on the computer screens. For this experiment, two videos have been used and displayed. In a few studies, the experiment for visual crowding has been considered to select the scenes that seem to be more naturalistic. This laboratory experiment aims to identify the average body categorisation performance that is measured in the target alone and the crowded experimental conditions.

Discussion on Visual Crowding Lab Report

In this experiment, a total number of 393 subjects have participated that were undergraduate psychology students. The two sets of pre-recorded movies, videos were presented in stimulus pairs that were accessed remotely through an online platform and viewed using the participants’ device and the procedure was based on multiple trials. The experiment presentation movie that was pre-recorded consisted of a sequence of 80 male target bodies. These bodies were physique simulated that had either very low muscle mass male body or a very high muscle mass body. The low muscle mass was estimated to be 16.5 kg/m2 and the high muscle mass were 30 kg/m2. In a study presented by Rashal & Yeshurun, (2014), the findings suggested that the considerable unpredictability in the aloofness over which features are incorporated generally depends on the properties of a stimulus. Therefore, a considerable fluctuation could be seen in the amount of visual crowding immensely between the two dissimilar scenes or even the objects that have been placed within the same scene. For understanding how the crowding can potentially limit a visual perception, it is essential to get to know and develop an understanding regarding how multiple stimulus manipulations could make an impact on the visual crowding and what is the combined impact of such manipulations on the visual crowding. This has been considered to be very essential for the following two reasons. The first reason for this is the real-world scenes have the potential to combine various properties of the objects in some ways. To support this Rashal & Yeshurun, (2014) have given an example that says a flanker could be dissimilar from the target in terms of spatial frequency and orientation, concurrently. In addition to this, it has also been found that effective presentation durations could be varied a lot. This variation can occur because of the blink of eyes, movements of the spectator, or objects. There are chances of the occurrence of masking and this often happens when the objects or its flankers have been occluding by some other moving objects. To focus on understanding the limitations regarding the recognition of the object in the real world, it is thus considered to be very important for understanding the effects of the combination of the properties of a stimulus. The second reason is that the degree of the effects regarding different properties of the stimulus on visual crowding could be compared only across the studies if they have been either completely independent of each other or if the effect of combination has been exactly understood regarding the combination.

When this experiment movie was started, a series of screens have appeared that instructed the participant for maintaining their gaze and fix up their eyes on the red fixation dot all through each trial sequence. Out of the 393 participants the data sets were submitted to the online data repository, there were total 106 that had certain formatting errors. Therefore, the data from the remaining 287 separate participants were considered for further analysis. Two conditions were taken and in half of the experimental trials, the target bodies were offered in the isolation and this was termed as Target Alone trials or Target Alone condition and in the other half trials the target bodies were convoyed by eight adjoining distracter bodies and this was termed as Crowded trials or Crowded trials. The findings of the experiment showed that the averaged across participants the proportion regarding the categorisations of the correct body in the target alone condition was 0.79 (S.D. = 0.17) and in the crowded condition it is 0.54 (S.D. = 0.10). The results of the findings for the performance of the average body categorisation that has been measured in the target alone and the crowded experimental conditions have been shown graphically in figure 1. The error bars that represent the performance of the standard deviation of categorisation that has been observed between the participants have also been shown graphically in Figure 1. For this experiment, a repeated t-test that is one-tailed has been conducted to determine that in which condition either target alone condition or the crowded condition, the categorisation of the body performance was better. The results that were gained from the findings of this experiment has been concluded that this analysis specifies that categorisation of the performance of the body was better in the target alone condition than in the crowded condition.

References for Visual Crowding Lab Report

Attwood, J. E., Kennard, C., Harris, J., Humphreys, G., & Antoniades, C. A. (2018). A Comparison of Change Blindness in Real-World and On-Screen Viewing of Museum Artefacts. Frontiers in Psychology9, 151. https://doi.org/10.3389/fpsyg.2018.00151

Harrison, W. J., & Bex, P. J. (2017). Visual crowding is a combination of an increase of positional uncertainty, source confusion, and featural averaging. Scientific reports7, 45551. https://doi.org/10.1038/srep45551Harrison, W. J., & Bex, P. J. (2017). Visual crowding is a combination of an increase of positional uncertainty, source confusion, and featural averaging. Scientific Reports7, 45551. https://doi.org/10.1038/srep45551

Levi, D.M. (2008) Crowding – an essential bottleneck for object recognition: a mini-review. Vision Res. 48, 635–654

Rashal, E., & Yeshurun, Y. (2014). Contrast dissimilarity effects on crowding are not simply 754 another case of target saliency. Journal of Vision, 14(6) doi:10.1167/14.6.9

Whitney, D., & Levi, D. M. (2011). Visual crowding: a fundamental limit on conscious perception and object recognition. Trends in Cognitive Sciences15(4), 160–168. https://doi.org/10.1016/j.tics.2011.02.005

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