The study of yacht shape feature based on eye tracking experiments

2017 ◽  
Author(s):  
Shu-Jiang Li ◽  
Hai-Yan Li ◽  
Wei-Min Yang
Keyword(s):  
Eye Tracking ◽  
Shape Feature ◽  
Feature Based

Optimization of Image Zernike Moments Shape Feature Based on Evolutionary Computation

2013 ◽  
pp. 199-216
Author(s):  
Maofu Liu ◽  
Huijun Hu
Keyword(s):  
Image Analysis ◽  
Evolutionary Computation ◽  
High Dimension ◽  
Optimization Algorithm ◽  
Feature Vector ◽  
Zernike Moments ◽  
Shape Feature ◽  
Original Image ◽  
Feature Based ◽  
Image Shape

The image shape feature can be described by the image Zernike moments. In this chapter, the authors point out the problem that the high dimension image Zernike moments shape feature vector can describe more detail of the original image but has too many elements making trouble for the next image analysis phases. Then the low dimension image Zernike moments shape feature vector should be improved and optimized to describe more detail of the original image. Therefore, the optimization algorithm based on evolutionary computation is designed and implemented in this chapter to solve this problem. The experimental results demonstrate the feasibility of the optimization algorithm.

Escaping the corner of death? An eye-tracking study of reading direction influence on attention and memory

2017 ◽  
Vol 34 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Monica D. Hernandez ◽  
Yong Wang ◽  
Hong Sheng ◽  
Morris Kalliny ◽  
Michael Minor
Keyword(s):  
Eye Tracking ◽  
Design Methodology ◽  
Attention And Memory ◽  
Cognitive Responses ◽  
Tracking Data ◽  
Bias Effect ◽  
Content Type ◽  
Reading Direction ◽  
Feature Based ◽  
The Web

Purpose The authors aim to examine the effect of location-driven logo placement on attention and memory on the web addressing differences between individuals that read unidirectionally (left-to-right [LTR]) versus bidirectionally (both right-to-left and LTR). Design/methodology/approach Using an eye-tracking approach combined with traditional verbal measures, the authors compared attention and memory measures from a sample composed of bidirectional (Arab/English) readers and unidirectional readers. Findings The findings reveal that unidirectional and bidirectional readers differ in attention patterns. Compared to bidirectional readers, unidirectional readers pay less attention to the logo on the bottom right corner of the webpage based on verbal measures. The eye-tracking data of the two groups further identify differences based on total hits and duration time. Unidirectional LTR readers demonstrate higher fluency in feature-based attention whereas bidirectional readers show higher fluency in spatial attention. Originality/value The authors expand on scarce research on reading direction bias effect on location-driven stimuli placement in online settings. They contribute to the understanding of the differences between unidirectional and bidirectional readers in their cognitive responses (attention and memory) to organization of marketing stimuli.

A216 Automatic Construction Method for Image and Shape Feature based Landmark

2015 ◽  
Vol 2015.14 (0) ◽  
pp. 273-276
Author(s):  
Daichi Abe ◽  
Satoshi Suzuki ◽  
Kouzirou Iizuka ◽  
Takashi Kawamura
Keyword(s):  
Construction Method ◽  
Shape Feature ◽  
Automatic Construction ◽  
Feature Based

scholarly journals An eye-tracking study of feature-based choice in one-shot games

2015 ◽  
Vol 19 (1) ◽  
pp. 177-201 ◽  
Author(s):  
Giovanna Devetag ◽  
Sibilla Di Guida ◽  
Luca Polonio
Keyword(s):  
Eye Tracking ◽  
Feature Based
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