scholarly journals Chinese-reading Expertise Modulates the Crowding Effect of Chinese Characters on Face Categorization

2018 ◽  
Author(s):  
Hsin-Mei Sun ◽  
Benjamin Balas
Keyword(s):  
Visual Information ◽  
Chinese Character ◽  
Peripheral Vision ◽  
Chinese Characters ◽  
Object Representations ◽  
Crowding Effect ◽  
Visual Expertise ◽  
Processing Style ◽  
Face Categorization ◽  
High Level

Crowding refers to the inability to recognize an object in peripheral vision when other objects are presented nearby. Studies have shown that crowding can be influenced by both low-level visual features and high-level object representations. In the current study, we tested how visual expertise affects crowding. We had native Chinese and non-Chinese readers perform a gender categorization task, in which they categorized target faces flanked by faces or Chinese characters that were presented upright or inverted. The results showed an effect of target-flanker similarity on crowding, as all participants performed worse when target faces were crowded by face compared to Chinese character flankers. The results also showed that native Chinese readers, but not non-Chinese readers, experienced more crowding when target faces were surrounded by upright compared to inverted face or Chinese character flankers, suggesting that participants’ visual expertise with the flanking stimuli along with their perceptual processing style shaped by cultures play an influential role in modulating the crowding effect. Our results support recent research showing that crowding is susceptible to both low- and high-level visual information.

scholarly journals Differential Representations of Perceived and Retrieved Visual Information in Hippocampus and Cortex

2018 ◽  
Vol 29 (10) ◽  
pp. 4452-4461 ◽  
Author(s):  
Sue-Hyun Lee ◽  
Dwight J Kravitz ◽  
Chris I Baker
Keyword(s):  
Visual Cortex ◽  
Visual Information ◽  
Response Patterns ◽  
Object Representations ◽  
Object Identity ◽  
Retrieval Process ◽  
Ultra High Field ◽  
Neural Populations ◽  
High Level ◽  
Cortical Representations

Abstract Memory retrieval is thought to depend on interactions between hippocampus and cortex, but the nature of representation in these regions and their relationship remains unclear. Here, we performed an ultra-high field fMRI (7T) experiment, comprising perception, learning and retrieval sessions. We observed a fundamental difference between representations in hippocampus and high-level visual cortex during perception and retrieval. First, while object-selective posterior fusiform cortex showed consistent responses that allowed us to decode object identity across both perception and retrieval one day after learning, object decoding in hippocampus was much stronger during retrieval than perception. Second, in visual cortex but not hippocampus, there was consistency in response patterns between perception and retrieval, suggesting that substantial neural populations are shared for both perception and retrieval. Finally, the decoding in hippocampus during retrieval was not observed when retrieval was tested on the same day as learning suggesting that the retrieval process itself is not sufficient to elicit decodable object representations. Collectively, these findings suggest that while cortical representations are stable between perception and retrieval, hippocampal representations are much stronger during retrieval, implying some form of reorganization of the representations between perception and retrieval.

scholarly journals Object-level visual information gets through the bottleneck of crowding

2011 ◽  
Vol 106 (3) ◽  
pp. 1389-1398 ◽  
Author(s):  
Jason Fischer ◽  
David Whitney
Keyword(s):  
Visual Processing ◽  
Visual Information ◽  
Neural Mechanisms ◽  
Visual Features ◽  
Object Representations ◽  
Dense Array ◽  
Processing Stream ◽  
High Level ◽  
Fundamental Limitation ◽  
Object Level

Natural visual scenes are cluttered. In such scenes, many objects in the periphery can be crowded, blocked from identification, simply because of the dense array of clutter. Outside of the fovea, crowding constitutes the fundamental limitation on object recognition and is thought to arise from the limited resolution of the neural mechanisms that select and bind visual features into coherent objects. Thus it is widely believed that in the visual processing stream, a crowded object is reduced to a collection of dismantled features with no surviving holistic properties. Here, we show that this is not so: an entire face can survive crowding and contribute its holistic attributes to the perceived average of the set, despite being blocked from recognition. Our results show that crowding does not dismantle high-level object representations to their component features.

Peripheral Vision in Martial Arts Experts: The Cost-Dependent Anchoring of Gaze

2019 ◽  
Vol 41 (3) ◽  
pp. 137-145 ◽  
Author(s):  
Thomas Hausegger ◽  
Christian Vater ◽  
Ernst-Joachim Hossner
Keyword(s):  
Martial Arts ◽  
Visual Information ◽  
Peripheral Vision ◽  
Cost Benefit ◽  
Gaze Behavior ◽  
Tae Kwon Do ◽  
Kung Fu ◽  
Gaze Anchoring ◽  
High Level ◽  
The Cost

Research on martial arts has suggested that gaze anchoring is functional for optimizing the use of peripheral visual information. The current study predicted that the height of gaze anchoring on the opponent’s body would depend on the potential attacking locations that need to be monitored. To test this prediction, the authors compared high-level athletes in kung fu (Qwan Ki Do), who attack with their arms and legs, with Tae Kwon Do fighters, who attack mostly with their legs. As predicted, the results show that Qwan Ki Do athletes anchor their gaze higher than Tae Kwon Do athletes do before and even during the first attack. In addition, gaze anchoring seems to depend on 3 factors: the particulars of the evolving situation, crucial cues, and specific visual costs (especially suppressed information pickup during saccades). These 3 factors should be considered in future studies on gaze behavior in sports to find the most functional, that is, cost-benefit-optimized, gaze pattern.

Exploring The Effect of Visual Information Degradation on Human Perception and Performance In A Human-Telerobot System

2020 ◽  
Vol 64 (1) ◽  
pp. 1302-1307
Author(s):  
Richard Stone ◽  
Minglu Wang ◽  
Thomas Schnieders ◽  
Esraa Abdelall
Keyword(s):  
Visual Information ◽  
Human Perception ◽  
Low Level ◽  
Hit Rate ◽  
Word Level ◽  
Level Of Automation ◽  
Significant Difference ◽  
Human Operators ◽  
And Performance ◽  
High Level

Human-robotic interaction system are increasingly becoming integrated into industrial, commercial and emergency service agencies. It is critical that human operators understand and trust automation when these systems support and even make important decisions. The following study focused on human-in-loop telerobotic system performing a reconnaissance operation. Twenty-four subjects were divided into groups based on level of automation (Low-Level Automation (LLA), and High-Level Automation (HLA)). Results indicated a significant difference between low and high word level of control in hit rate when permanent error occurred. In the LLA group, the type of error had a significant effect on the hit rate. In general, the high level of automation was better than the low level of automation, especially if it was more reliable, suggesting that subjects in the HLA group could rely on the automatic implementation to perform the task more effectively and more accurately.

A comparison of the changes in the patterns of the usage and categorization of the classifier ‘ben 本’ in Korean, Chinese, and Japanese

2021 ◽  
Vol 5 (1) ◽  
pp. 43-51
Author(s):  
Jeong-A Jo
Keyword(s):  
Cultural Differences ◽  
Chinese Character ◽  
Chinese Characters ◽  
Common Features ◽  
The World ◽  
The Common ◽  
Korean Chinese ◽  
The Relationship

This study aims to examine the common features and differences in how the Chinese-character classifier ‘ ben 本’ is used in Chinese, Korean, and Japanese, and will explore the factors that have affected the categorization processes and patterns of the classifier ‘ ben 本.’ Consideration of the differences in the patterns of usage and categorization of the same Chinese classifier in different languages enables us to look into the perception of the world and the socio cultural differences inherent in each language, the differences in the perception of Chinese characters, and the relationship between classifiers.

A comparative study of children’s Chinese character textbooks in Korea and China, with a focus on Yu Hap

2021 ◽  
Vol 5 (2) ◽  
pp. 145-153
Author(s):  
Jeong Yeon Sil ◽  
Jang Eun Young ◽  
Park Heung Soo
Keyword(s):  
Comparative Analysis ◽  
Comparative Study ◽  
Chinese Character ◽  
Significant Proportion ◽  
Written Language ◽  
Chinese Characters ◽  
Children's Books ◽  
High Learning ◽  
Modern Chinese ◽  
Ancient Times

This study examines why and how Chinese characters spread into Korea. It subsequently conducts a comparative analysis of Korean and Chinese children’s textbooks with a focus on Yu Hap from the perspective of the acceptance and acculturation of Chinese characters. It also explores how commonly used the characters in Yu Hap are, and the text’s learning value as one of Korea’s children’s textbooks. Yu Hap is very significant as the first written language textbook published in Korea. A comparative analysis of the characters used in four children’s books published in Korea found that the characters in Yu Hap are very common, and the text has a high learning value. Approximately 50% of the characters in San Bai Qian and Yu Hap are the same, showing that both China and Korea had similar perceptions of the characters in common use. A very significant proportion of characters overlap in Basic Chinese Character for Educational Use, List of Common Words in Modern Chinese, and Yu Hap; this supports the idea that the same characters have continued to be used from ancient times to the present day.

scholarly journals Chinese Character Image Completion Using a Generative Latent Variable Model

2021 ◽  
Vol 11 (2) ◽  
pp. 624
Author(s):  
In-su Jo ◽  
Dong-bin Choi ◽  
Young B. Park
Keyword(s):  
Latent Variable ◽  
Chinese Character ◽  
Image Inpainting ◽  
Latent Variable Model ◽  
Chinese Characters ◽  
Image Completion ◽  
Variable Model ◽  
Variational Autoencoder ◽  
Convolution Model ◽  
Detection Technologies

Chinese characters in ancient books have many corrupted characters, and there are cases in which objects are mixed in the process of extracting the characters into images. To use this incomplete image as accurate data, we use image completion technology, which removes unnecessary objects and restores corrupted images. In this paper, we propose a variational autoencoder with classification (VAE-C) model. This model is characterized by using classification areas and a class activation map (CAM). Through the classification area, the data distribution is disentangled, and then the node to be adjusted is tracked using CAM. Through the latent variable, with which the determined node value is reduced, an image from which unnecessary objects have been removed is created. The VAE-C model can be utilized not only to eliminate unnecessary objects but also to restore corrupted images. By comparing the performance of removing unnecessary objects with mask regions with convolutional neural networks (Mask R-CNN), one of the prevalent object detection technologies, and also comparing the image restoration performance with the partial convolution model (PConv) and the gated convolution model (GConv), which are image inpainting technologies, our model is proven to perform excellently in terms of removing objects and restoring corrupted areas.

A research on an intelligent recognition tool for bronze inscriptions of the Shang and Zhou dynasties

2020 ◽  
Vol 4 (4) ◽  
pp. 271-279
Author(s):  
Rui Guo
Keyword(s):  
Computer Technology ◽  
Character Recognition ◽  
Chinese Character ◽  
Research Process ◽  
Chinese Characters ◽  
Chinese Character Recognition ◽  
The World ◽  
Bronze Inscriptions ◽  
Intelligent Recognition ◽  
Functional Components

The intelligent recognition tool for bronze inscriptions of the Shang and Zhou dynasties—the “Shang Zhou Bronze Inscriptions Intelligent Mirror”—was successfully invented in Shanghai. This mirror, based on the computer technology of artificial intelligence (AI) image recognition and image retrieval, succeeds in automagical recognition of bronze inscriptions, both single letters and full texts. This research leads the trend of the AI recognition of Ancient Chinese characters and accumulates valuable experience for the development of inter-disciplinary research on Chinese character recognition. This essay emphasizes the importance of the bronze inscriptions of the Shang and Zhou dynasty database in the AI recognition of bronze inscriptions, introduces the functional components of this tool, and shares the whole research process in order to offer experience for the related research on AI recognition of other types of Ancient Chinese characters as well as ideographs in the world scope. “Shang Zhou Bronze Inscriptions Intelligent Mirror” as a tool for bronze inscription recognition also has room for improvement and support, and guidance from experts in similar areas is greatly welcomed.

A comparison of the changes in the patterns of the usage and categorization of the classifier ‘ben 本’ in Korean, Chinese, and Japanese

2021 ◽  
pp. 251385022098177
Author(s):  
Jeong-A Jo
Keyword(s):  
Cultural Differences ◽  
Chinese Character ◽  
Chinese Characters ◽  
Common Features ◽  
The World ◽  
The Common ◽  
Korean Chinese ◽  
The Relationship

This study aims to examine the common features and differences in how the Chinese-character classifier ‘ ben 本’ is used in Chinese, Korean, and Japanese, and will explore the factors that have affected the categorization processes and patterns of the classifier ‘ ben 本.’ Consideration of the differences in the patterns of usage and categorization of the same Chinese classifier in different languages enables us to look into the perception of the world and the socio cultural differences inherent in each language, the differences in the perception of Chinese characters, and the relationship between classifiers.

On-Line Chinese Character Recognition Via a Representation of Spatial Relationships Between Strokes

1997 ◽  
Vol 11 (03) ◽  
pp. 329-357 ◽  
Author(s):  
Ju-Wei Chen ◽  
Suh-Yin Lee
Keyword(s):  
Character Recognition ◽  
Chinese Character ◽  
Spatial Relationship ◽  
Spatial Relations ◽  
Chinese Characters ◽  
Spatial Relationships ◽  
Matching Problem ◽  
Structural Rules ◽  
Chinese Character Recognition ◽  
On Line

Chinese characters are constructed by basic strokes based on structural rules. In handwritten characters, the shapes of the strokes may vary to some extent, but the spatial relations and geometric configurations of the strokes are usually maintained. Therefore these spatial relations and configurations could be regarded as invariant features and could be used in the recognition of handwritten Chinese characters. In this paper, we investigate the structural knowledge in Chinese characters and propose the stroke spatial relationship representation (SSRR) to describe Chinese characters. An On-Line Chinese Character Recognition (OLCCR) method using the SSRR is also presented. With SSRR, each character is processed and is represented by an attribute graph. The process of character recognition is thereby transformed into a graph matching problem. After careful analysis, the basic spatial relationship between strokes can be characterized into five classes. A bitwise representation is adopted in the design of the data structure to reduce storage requirements and to speed up character matching. The strategy of hierarchical search in the preclassification improves the recognition speed. Basically, the attribute graph model is a generalized character representation that provides a useful and convenient representation for newly added characters in an OLCCR system with automatic learning capability. The significance of the structural approach of character recognition using spatial relationships is analyzed and is proved by experiments. Realistic testing is provided to show the effectiveness of the proposed method.

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