Working Memory-Driven Attention in Real-World Search

Perception ◽  
2018 ◽  
Vol 47 (9) ◽  
pp. 966-975 ◽  
Author(s):  
Shinyoung Jung ◽  
Yosun Yoon ◽  
Suk Won Han

People’s attention is well attracted to stimuli matching their working memory. This memory-driven attentional capture has been demonstrated in simplified and controlled laboratory settings. The present study investigated whether working memory contents capture attention in a setting that closely resembles real-world environment. In the experiment, participants performed a task of searching for a target object in real-world indoor scenes, while maintaining a visual object in working memory. To create a setting similar to real-world environment, images taken from IKEA®’s online catalogue were used. The results showed that participants’ attention was biased toward a working memory-matching object, interfering with the target search. This was so even when participants did not expect that a memory-matching stimulus would appear in the search array. These results suggest that working memory can bias attention in complex, natural environment and this memory-driven attentional capture in real-world setting takes place in an automatic manner.

2017 ◽  
Vol 17 (10) ◽  
pp. 671
Author(s):  
Shinyoung Jung ◽  
Yosun Yoon ◽  
Suk Won Han

2019 ◽  
Vol 2019 (1) ◽  
pp. 237-242
Author(s):  
Siyuan Chen ◽  
Minchen Wei

Color appearance models have been extensively studied for characterizing and predicting the perceived color appearance of physical color stimuli under different viewing conditions. These stimuli are either surface colors reflecting illumination or self-luminous emitting radiations. With the rapid development of augmented reality (AR) and mixed reality (MR), it is critically important to understand how the color appearance of the objects that are produced by AR and MR are perceived, especially when these objects are overlaid on the real world. In this study, nine lighting conditions, with different correlated color temperature (CCT) levels and light levels, were created in a real-world environment. Under each lighting condition, human observers adjusted the color appearance of a virtual stimulus, which was overlaid on a real-world luminous environment, until it appeared the whitest. It was found that the CCT and light level of the real-world environment significantly affected the color appearance of the white stimulus, especially when the light level was high. Moreover, a lower degree of chromatic adaptation was found for viewing the virtual stimulus that was overlaid on the real world.


2015 ◽  
Vol 47 (10) ◽  
pp. 1223 ◽  
Author(s):  
Wei ZHANG ◽  
Bingping ZHOU ◽  
Ling ZANG ◽  
Shuliang MO

2021 ◽  
Vol 11 (10) ◽  
pp. 4617
Author(s):  
Daehee Park ◽  
Cheoljun Lee

Because smartphones support various functions, they are carried by users everywhere. Whenever a user believes that a moment is interesting, important, or meaningful to them, they can record a video to preserve such memories. The main problem with video recording an important moment is the fact that the user needs to look at the scene through the mobile phone screen rather than seeing the actual real-world event. This occurs owing to uncertainty the user might feel when recording the video. For example, the user might not be sure if the recording is of high-quality and might worry about missing the target object. To overcome this, we developed a new camera application that utilizes two main algorithms, the minimum output sum of squared error and the histograms of oriented gradient algorithms, to track the target object and recognize the direction of the user’s head. We assumed that the functions of the new camera application can solve the user’s anxiety while recording a video. To test the effectiveness of the proposed application, we conducted a case study and measured the emotional responses of users and the error rates based on a comparison with the use of a regular camera application. The results indicate that the new camera application induces greater feelings of pleasure, excitement, and independence than a regular camera application. Furthermore, it effectively reduces the error rates during video recording.


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