Informatics Publishing Limited

Faris A. Abuhashish ¹, Jamal Zraqou ², Wesam Alkhodour ², Mohd S. Sunar ¹, Hoshang Kolivand ¹

Affiliations
1 Magicx, Universiti Teknologi Malaysia, Johor Bahru, MY
2 Department of Multimedia, Isra University, Amman, JO

Abstract

Human computer interaction (HCI) considered main aspect in virtual reality (VR) especially in the context of emotion, where users can interact with virtual reality through their emotions and it could be expressed in virtual reality. Last decade many researchers focused on emotion classification in order to employ emotion in interaction with virtual reality, the classification will be done based on Electroencephalogram (EEG) brain signals. This paper provides a new hybrid emotion classification method by combining selfassessment, arousal valence dimension and variance of brain hemisphere activity to classify users' emotions. Self-assessment considered a standard technique used for assessing emotion, arousal valence emotion dimension model is an emotion classifier with regards to aroused emotions and brain hemisphere activity that classifies emotion with regards to right and left hemisphere. This method can classify human emotions, two basic emotions is highlighted i.e. happy and sad. EEG brain signals are used to interpret the users' emotional. Emotion interaction is expressed by 3D model walking expression in VR. The results show that the hybrid method classifies the highlighted emotions in different circumstances, and how the 3D model changes its walking style according to the classified users' emotions. Finally, the outcome is believed to afford new technique on classifying emotions with feedback through 3D virtual model walking expression.

Keywords

3D Virtual Model, Virtual Reality, Walking, BCI, Emotion.

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Hasan Z. H. Alhajhamad ¹, Faris Amin Abu Hashish ¹, Hoshang Kolivand ¹, Mohd Shahrizal Sunar ¹

Affiliations
1 Universiti Teknologi Malaysia, Skudai, Johor 81310, MY

Abstract

This work is an accumulative study on some techniques which could help to extract the geometry and color of an image in the real-time environment. Image segmentation is a hot-zone in Computer Vision approach, however, works still on to produce accurate segmentation results for images. In corporation with other surveys which compares multiple techniques, this paper takes the advantage of choosing the most appropriate technique(s) to be adopted for Augmented Reality environment.Interested reader will obtain knowledge on various categories and types of research challenges in the image-based segmentation within the scope of AR environments.

Keywords

Segmentation, Intensity, Color, Photometry, and Thresholding, Augmented Reality (AR).

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