scholarly journals Delivering a Unified Design Model (UDM) - To Align Design to the Way the Human Brain Processes Visual Information

2017 ◽  
Author(s):  
Bruce Hilliard ◽  
Jocelyn Armarego ◽  
Andrew Turk ◽  
Tanya McGill
Author(s):  
Maria Elizabeth Grabe ◽  
Ozen Bas

The focus of this chapter is on how changes in the media landscape have forced the reconsideration of the way in which ‘memory’, ‘knowledge’, and ‘informed citizenship’ are understood, defined, and researched. Thus, for example, journalism needs to take account of the phenomenon of so-called news grazing (the active consumption of news by flipping through channels and skipping unwanted material) and that of incidental news exposure (unintended exposure to news when media users go online for non-news functions). Traditional views of informed citizenship (as simply acquiring appropriate facts and information) are challenged by calls to include applied understanding and comprehension of social issues and emotional responses to those issues. The chapter is critical of an excessive reliance on verbal tests of memory and stresses the need to develop visual measures, given that the human brain is better adapted for visual than verbal processing.


Author(s):  
Hiroto Namihira

This chapter proposes a new educational methodology for theoretical contents. It aims to effectively transmit theoretical content meanings. Here, the effects of content visualization enhance the transmission of meaning. By processing visual information, the human brain can immediately understand the mutual relationships between elements in addition to the whole meaning. Comprehension becomes increasingly effective when movement is added to static information. The new educational methodology proposed here is based on such visualization. It is called “The Dynamic Visualization Method.” It is designed so students can visually set allowable conditions before processing them. This selective freedom enables students to extract their hidden leaning interests. Mathematical processes were used to verify the effectiveness of this methodology. A variety of items were thus adopted ranging from the elementary-school to university levels. The contents of those items are visualized in this chapter. The educational effects are then discussed.


Author(s):  
QI ZHANG ◽  
KEN MOGI

Human ability to process visual information of outside world is yet far ahead of man-made systems in accuracy and speed. In particular, human beings can perceive 3-D object from various cues, such as binocular disparity and monocular shading cues. Understanding of the mechanism of human visual processing will lead to a breakthrough in creating artificial visual systems. Here, we study the human 3-D volumetric object perception that is induced by a visual phenomenon named as the pantomime effect and by the monocular shading cues. We measured human brain activities using fMRI when the subjects were observing the visual stimuli. A coordinated system of brain areas, including those in the prefrontal and parietal cortex, in addition to the occipital visual areas was found to be involved in the volumetric object perception.


2017 ◽  
Vol 17 (3) ◽  
pp. 70-77 ◽  
Author(s):  
M. A. Mukutadze ◽  
◽  
A. N. Garmonina ◽  
V. M. Prikhodko ◽  
◽  
...  

2019 ◽  
Vol 8 (1) ◽  
pp. 50-54
Author(s):  
Ashok Kumar Bathla . ◽  
Sunil Kumar Gupta .

Optical Character Recognition (OCR) technology allows a computer to “read” text (both typed and handwritten) the way a human brain does.Significant research efforts have been put in the area of Optical Character Segmentation (OCR) of typewritten text in various languages, however very few efforts have been put on the segmentation and skew correction of handwritten text written in Devanagari which is a scripting language of Hindi. This paper aims a novel technique for segmentation and skew correction of hand written Devanagari text. It shows the accuracy of 91% and takes less than one second to segment a particular handwritten word.


Author(s):  
Javier Ruiz-del-Solar ◽  
◽  
Aureli Soria-Frisch ◽  

Simultaneous progress in sensor and signal processing technologies stimulates the implementation of more refined pattern recognition systems in order to solve problems of increasing complexity. The progress on both technologies induced the implementation of the here presented framework for the fusion of infrared and color textural information. The framework is based on different aspects of the processing of visual information in the human brain. Some organizational principles of multisensorial information fusion in higher associative areas are also reflected in it. Preliminary results, realized in a simplified framework, show the validity of the biological-based approach in the resolution of multisensorial image fusion.


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