Current Issue : October - December Volume : 2014 Issue Number : 4 Articles : 5 Articles
We present a large-scale quantitative contextual survey of the geocaching community in Germany, one of the world�s largest\ngeocaching communities.We investigate the features, attitudes, interests, andmotivations that characterise theGerman geocachers.\nTwo anonymous surveys have been carried out on this issue in the year 2007.We conducted a large-scale qualitative general study\nbased on web questionnaires and amore targeted study, which aimed at a comprehensive amount of revealed geocaches of a certain\nregion. With sample sizes of n = 1982 (study 1: general study) and n = 310 (study 2: regional study) we provide a representative\nbasis to ground previous qualitative research in this domain. In addition, we investigated the usage of technology in combination\nwith traditional paper-based media by the geocachers. This knowledge can be used to reflect on past and future trends within the\ngeocaching community....
To improve the human-computer interaction (HCI) to be as good as human-human interaction, building an efficient approach\nfor human emotion recognition is required.These emotions could be fused from several modalities such as facial expression, hand\ngesture, acoustic data, and biophysiological data. In this paper, we address the frame-based perception of the universal human facial\nexpressions (happiness, surprise, anger, disgust, fear, and sadness), with the help of several geometrical features. Unlike many other\ngeometry-based approaches, the frame-based method does not rely on prior knowledge of a person-specific neutral expression;\nthis knowledge is gained through human intervention and not available in real scenarios. Additionally, we provide a method to\ninvestigate the performance of the geometry-based approaches under various facial point localization errors. From an evaluation\non two public benchmark datasets, we have found that using eight facial points, we can achieve the state-of-the-art recognition\nrate. However, this state-of-the-art geometry-based approach exploits features derived from 68 facial points and requires prior\nknowledge of the person-specific neutral expression.Theexpression recognition rate using geometrical features is adversely affected\nby the errors in the facial point localization, especially for the expressions with subtle facial deformations....
Context-aware applications are required to be aware of user context and ambient intelligent to support nonintrusive humancomputer\ninteraction. However, the uncertain real-world environments make it difficult for a system to perceive enough\nenvironmental contexts and achieve user�s goal. Therefore, this study proposes a framework for developing an NFC-enabled\nintelligent agent, which combines the NFC technique with context-acquisition, ontology-knowledgebase, and semantic-adaptation\nmodules to be aware of location, time, device, and activity contexts with respect to personal and social profiles. To cope with the\nuncertain environment, a credit-based incentive scheme is also proposed to encourage social cooperation and thereby enlarge\nthe value of personal perceptions. By developing a complete ontology knowledgebase, the proposed framework can incorporate\nwith social-cooperation schemes to recommend relevant services for supporting reactive action, proactive achievement, and social\ncooperation.The resultant social-advertising system shows that this framework can support a wide-range of different functionalities\nand is indispensable to an NFC-based intelligent agent for social Internet of things....
Hand gesture recognition is very significant for human-computer interaction. In this work, we present a novel real-time method for\nhand gesture recognition. In our framework, the hand region is extracted from the background with the background subtraction\nmethod. Then, the palm and fingers are segmented so as to detect and recognize the fingers. Finally, a rule classifier is applied to\npredict the labels of hand gestures. The experiments on the data set of 1300 images show that our method performs well and is\nhighly efficient. Moreover, our method shows better performance than a state-of-art method on another data set of hand gestures....
In today�s technologically driven world, there is a need to better understand the ways that common computer malfunctions affect\ncomputer users. These malfunctions may have measurable influences on computer user�s cognitive, emotional, and behavioral\nresponses. An experiment was conducted where participants conducted a series of web search tasks while wearing functional nearinfrared\nspectroscopy (fNIRS) and galvanic skin response sensors. Two computer malfunctionswere introduced during the sessions\nwhich had the potential to influence correlates of user trust and suspicion. Surveys were given after each session to measure user�s\nperceived emotional state, cognitive load, and perceived trust. Results suggest that fNIRS can be used to measure the different\ncognitive and emotional responses associated with computer malfunctions. These cognitive and emotional changes were correlated\nwith users� self-report levels of suspicion and trust, and they in turn suggest future work that further explores the capability of\nfNIRS for the measurement of user experience during human-computer interactions....
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