scholarly journals Object Frequency and Predictability Effects on Eye Fixation Durations in Real-World Scene Viewing

2010 ◽  
Vol 3 (3) ◽  
Author(s):  
Hsueh-Cheng Wang ◽  
Alex D. Hwang ◽  
Marc Pomplun
Keyword(s):  
Real World ◽  
Latent Semantic Analysis ◽  
Fixation Duration ◽  
Semantic Analysis ◽  
Scene Analysis ◽  
Eye Fixations ◽  
Fixation Durations ◽  
Scene Viewing ◽  
Direction Of Effects ◽  
Text Reading

During text reading, the durations of eye fixations decrease with greater frequency and predictability of the currently fixated word (Rayner, 1998; 2009). However, it has not been tested whether those results also apply to scene viewing. We computed object frequency and predictability from both linguistic and visual scene analysis (LabelMe, Russell et al., 2008), and Latent Semantic Analysis (Landauer et al., 1998) was applied to estimate predictability. In a scene-viewing experiment, we found that, for small objects, linguistics-based frequency, but not scene-based frequency, had effects on first fixation duration, gaze duration, and total time. Both linguistic and scene-based predictability affected total time. Similar to reading, fixation duration decreased with higher frequency and predictability. For large objects, we found the direction of effects to be the inverse of those found in reading studies. These results suggest that the recognition of small objects in scene viewing shares some characteristics with the recognition of words in reading.

Fixation Duration Is Related to Local Image Statistics During Real-World Scene Viewing

2004 ◽  
Author(s):  
James R. Brockmole ◽  
Michael L. Mack ◽  
Monica S. Castelhano ◽  
Aude Oliva ◽  
John M. Henderson
Keyword(s):  
Real World ◽  
Fixation Duration ◽  
Image Statistics ◽  
Scene Viewing ◽  
Local Image

Neural Correlates of Fixation Duration during Real-world Scene Viewing: Evidence from Fixation-related (FIRE) fMRI

2015 ◽  
Vol 27 (6) ◽  
pp. 1137-1145 ◽  
Author(s):  
John M. Henderson ◽  
Wonil Choi
Keyword(s):  
Eye Movements ◽  
Cognitive Processes ◽  
Fixation Duration ◽  
Computational Models ◽  
Scene Perception ◽  
Motor Planning ◽  
Active Vision ◽  
Saccadic Eye Movements ◽  
Scene Analysis ◽  
Scene Viewing

During active scene perception, our eyes move from one location to another via saccadic eye movements, with the eyes fixating objects and scene elements for varying amounts of time. Much of the variability in fixation duration is accounted for by attentional, perceptual, and cognitive processes associated with scene analysis and comprehension. For this reason, current theories of active scene viewing attempt to account for the influence of attention and cognition on fixation duration. Yet almost nothing is known about the neurocognitive systems associated with variation in fixation duration during scene viewing. We addressed this topic using fixation-related fMRI, which involves coregistering high-resolution eye tracking and magnetic resonance scanning to conduct event-related fMRI analysis based on characteristics of eye movements. We observed that activation in visual and prefrontal executive control areas was positively correlated with fixation duration, whereas activation in ventral areas associated with scene encoding and medial superior frontal and paracentral regions associated with changing action plans was negatively correlated with fixation duration. The results suggest that fixation duration in scene viewing is controlled by cognitive processes associated with real-time scene analysis interacting with motor planning, consistent with current computational models of active vision for scene perception.

scholarly journals Perceptual Switching, Eye Movements, and the Bus Paradox

Perception ◽  
10.1068/p5052 ◽  
2003 ◽  
Vol 32 (6) ◽  
pp. 681-698 ◽  
Author(s):  
Junji Ito ◽  
Andrey R Nikolaev ◽  
Marjolein Luman ◽  
Maartje F Aukes ◽  
Chie Nakatani ◽  
...  
Keyword(s):  
Eye Movements ◽  
Fixation Duration ◽  
Time Course ◽  
Sampling Bias ◽  
Moving Window ◽  
Random Event ◽  
Eye Fixations ◽  
Fixation Durations ◽  
Switching Behaviour ◽  
Blink Frequency

According to a widely cited finding by Ellis and Stark (1978 Perception7 575–581), the duration of eye fixations is longer at the instant of perceptual reversal of an ambiguous figure than before or after the reversal. However, long fixations are more likely to include samples of an independent random event than are short fixations. This sampling bias would produce the pattern of results also when no correlation exists between fixation duration and perceptual reversals. When an appropriate correction is applied to the measurement of fixation durations, the effect disappears. In fact, there are fewer actual button-presses during the long intervals than would be expected by chance. Moving-window analyses performed on eye-fixation data reveal that no unique eye event is associated with switching behaviour. However, several indicators, such as blink frequency, saccade frequency, and the direction of the saccade, are each differentially sensitive to perceptual and response-related aspects of the switching process. The time course of these indicators depicts switching behaviour as a process of cascaded stages.

Task Estimation Using Latent Semantic Analysis of Visual Scenes and Spoken Words

2012 ◽  
Vol 132 (9) ◽  
pp. 1473-1480
Author(s):  
Masashi Kimura ◽  
Shinta Sawada ◽  
Yurie Iribe ◽  
Kouichi Katsurada ◽  
Tsuneo Nitta
Keyword(s):  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Spoken Words ◽  
Visual Scenes

Similarity Detection Using Latent Semantic Analysis Algorithm

2018 ◽  
Vol 6 (8) ◽  
pp. 102
Author(s):  
Priyanka R. Patil ◽  
Shital A. Patil
Keyword(s):  
Latent Semantic Analysis ◽  
Latent Dirichlet Allocation ◽  
Semantic Analysis ◽  
Mining Method ◽  
Research Papers ◽  
Information Measures ◽  
Automated Software ◽  
Day By Day ◽  
Ways Of Life ◽  
Dirichlet Allocation

Similarity View is an application for visually comparing and exploring multiple models of text and collection of document. Friendbook finds ways of life of clients from client driven sensor information, measures the closeness of ways of life amongst clients, and prescribes companions to clients if their ways of life have high likeness. Roused by demonstrate a clients day by day life as life records, from their ways of life are separated by utilizing the Latent Dirichlet Allocation Algorithm. Manual techniques can't be utilized for checking research papers, as the doled out commentator may have lacking learning in the exploration disciplines. For different subjective views, causing possible misinterpretations. An urgent need for an effective and feasible approach to check the submitted research papers with support of automated software. A method like text mining method come to solve the problem of automatically checking the research papers semantically. The proposed method to finding the proper similarity of text from the collection of documents by using Latent Dirichlet Allocation (LDA) algorithm and Latent Semantic Analysis (LSA) with synonym algorithm which is used to find synonyms of text index wise by using the English wordnet dictionary, another algorithm is LSA without synonym used to find the similarity of text based on index. LSA with synonym rate of accuracy is greater when the synonym are consider for matching.

LATENT-SEMANTIC ANALYSIS, SOCIAL NETWORKS AND NON-STRUCTURED DATA: INTERACTION METHOD

2019 ◽  
Keyword(s):  
Social Networks ◽  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Statistical Processing ◽  
Unstructured Data ◽  
Average Score ◽  
Text Type ◽  
Internet Users ◽  
The Matrix ◽  
Human Thinking

This article examines the method of latent-semantic analysis, its advantages, disadvantages, and the possibility of further transformation for use in arrays of unstructured data, which make up most of the information that Internet users deal with. To extract context-dependent word meanings through the statistical processing of large sets of textual data, an LSA method is used, based on operations with numeric matrices of the word-text type, the rows of which correspond to words, and the columns of text units to texts. The integration of words into themes and the representation of text units in the theme space is accomplished by applying one of the matrix expansions to the matrix data: singular decomposition or factorization of nonnegative matrices. The results of LSA studies have shown that the content of the similarity of words and text is obtained in such a way that the results obtained closely coincide with human thinking. Based on the methods described above, the author has developed and proposed a new way of finding semantic links between unstructured data, namely, information on social networks. The method is based on latent-semantic and frequency analyzes and involves processing the search result received, splitting each remaining text (post) into separate words, each of which takes the round in n words right and left, counting the number of occurrences of each term, working with a pre-created semantic resource (dictionary, ontology, RDF schema, ...). The developed method and algorithm have been tested on six well-known social networks, the interaction of which occurs through the ARI of the respective social networks. The average score for author's results exceeded that of their own social network search. The results obtained in the course of this dissertation can be used in the development of recommendation, search and other systems related to the search, rubrication and filtering of information.

Web clustering based on hybrid probabilistic latent semantic analysis model

2013 ◽  
Vol 32 (11) ◽  
pp. 3018-3022 ◽  
Author(s):  
Zhi-he WANG ◽  
Ling-yun WANG ◽  
Hui DANG ◽  
Li-na PAN
Keyword(s):  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Probabilistic Latent Semantic Analysis ◽  
Analysis Model ◽  
Web Clustering
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