Abstract: One challenging direction of mobile commerce (mcommerce)
that is getting a great deal of attention globally is mobile
financing. The smart-phone and PDA users all around the world are
facing difficulties to become accustomed and trust in m-commerce.
The main rationale can be the slow variation and lack of trust in
mobile payment systems. Mobile payment systems that are in use
need to be more effective and efficient. This paper proposes: the
interface design is not the only factor affecting the m-commerce
adoption and lack of trust; in fact it is the combined effect of
interface usability and trustworthy mobile payment systems, because
it-s the money that the user has to spend at the end of the day, which
the user requires to get transferred securely. The purpose of this
research is to identify the problems regarding the trust and adaption
of m-commerce applications by mobile users and to provide the best
possible solution with respect to human computer interaction (HCI)
principles.
Abstract: In this paper we report a study aimed at determining
the effects of animation on usability and appeal of educational
software user interfaces. Specifically, the study compares 3
interfaces developed for the Mathsigner™ program: a static
interface, an interface with highlighting/sound feedback, and an
interface that incorporates five Disney animation principles. The
main objectives of the comparative study were to: (1) determine
which interface is the most effective for the target users of
Mathsigner™ (e.g., children ages 5-11), and (2) identify any Gender
and Age differences in using the three interfaces. To accomplish
these goals we have designed an experiment consisting of a
cognitive walkthrough and a survey with rating questions. Sixteen
children ages 7-11 participated in the study, ten males and six
females. Results showed no significant interface effect on user task
performance (e.g., task completion time and number of errors);
however, interface differences were seen in rating of appeal, with
the animated interface rated more 'likeable' than the other two.
Task performance and rating of appeal were not affected
significantly by Gender or Age of the subjects.
Abstract: Perceptions of quality from both designers and users
perspective have now stretched beyond the traditional usability,
incorporating abstract and subjective concepts. This has led to a shift
in human computer interaction research communities- focus; a shift
that focuses on achieving user experience (UX) by not only fulfilling
conventional usability needs but also those that go beyond them. The
term UX, although widely spread and given significant importance,
lacks consensus in its unified definition. In this paper, we survey
various UX definitions and modeling frameworks and examine them
as the foundation for proposing a UX evolution lifecycle framework
for understanding UX in detail. In the proposed framework we identify
the building blocks of UX and discuss how UX evolves in various
phases. The framework can be used as a tool to understand experience
requirements and evaluate them, resulting in better UX design and
hence improved user satisfaction.
Abstract: The increasing number of senior population gradually
causes to demand the use of information and communication
technology for their satisfactory lives. This paper presents the
development of an integrated TV based system which offers an
opportunity to provide value added services to a large number of
elderly citizens, and thus helps improve their quality of life. The
design philosophy underlying this paper is to fulfill both technological
and human aspects. The balance between these two dimensions has
been currently stressed as a crucial element for the design of usable
systems in real use, particularly to the elderly who have physical and
mental decline. As the first step to achieve it, we have identified
human and social factors that affect the elder-s quality of life by a
literature review, and based on them, build four fundamental services:
information, healthcare, learning and social network services.
Secondly, the system architecture, employed technologies and the
elderly-friendly system design considerations are presented. This
reflects technological and human perspectives in terms of the system
design. Finally, we describe some scenarios that illustrate the
potentiality of the proposed system to improve elderly people-s quality
of life.
Abstract: Distant-talking voice-based HCI system suffers from
performance degradation due to mismatch between the acoustic
speech (runtime) and the acoustic model (training). Mismatch is
caused by the change in the power of the speech signal as observed at
the microphones. This change is greatly influenced by the change in
distance, affecting speech dynamics inside the room before reaching
the microphones. Moreover, as the speech signal is reflected, its
acoustical characteristic is also altered by the room properties. In
general, power mismatch due to distance is a complex problem. This
paper presents a novel approach in dealing with distance-induced
mismatch by intelligently sensing instantaneous voice power variation
and compensating model parameters. First, the distant-talking speech
signal is processed through microphone array processing, and the
corresponding distance information is extracted. Distance-sensitive
Gaussian Mixture Models (GMMs), pre-trained to capture both
speech power and room property are used to predict the optimal
distance of the speech source. Consequently, pre-computed statistic
priors corresponding to the optimal distance is selected to correct
the statistics of the generic model which was frozen during training.
Thus, model combinatorics are post-conditioned to match the power
of instantaneous speech acoustics at runtime. This results to an
improved likelihood in predicting the correct speech command at
farther distances. We experiment using real data recorded inside two
rooms. Experimental evaluation shows voice recognition performance
using our method is more robust to the change in distance compared
to the conventional approach. In our experiment, under the most
acoustically challenging environment (i.e., Room 2: 2.5 meters), our
method achieved 24.2% improvement in recognition performance
against the best-performing conventional method.
Abstract: There are many researches to detect collision between real object and virtual object in 3D space. In general, these techniques are need to huge computing power. So, many research and study are constructed by using cloud computing, network computing, and distribute computing. As a reason of these, this paper proposed a novel fast 3D collision detection algorithm between real and virtual object using 2D intersection area. Proposed algorithm uses 4 multiple cameras and coarse-and-fine method to improve accuracy and speed performance of collision detection. In the coarse step, this system examines the intersection area between real and virtual object silhouettes from all camera views. The result of this step is the index of virtual sensors which has a possibility of collision in 3D space. To decide collision accurately, at the fine step, this system examines the collision detection in 3D space by using the visual hull algorithm. Performance of the algorithm is verified by comparing with existing algorithm. We believe proposed algorithm help many other research, study and application fields such as HCI, augmented reality, intelligent space, and so on.
Abstract: Human computer interaction has progressed
considerably from the traditional modes of interaction. Vision based
interfaces are a revolutionary technology, allowing interaction
through human actions, gestures. Researchers have developed
numerous accurate techniques, however, with an exception to few
these techniques are not evaluated using standard HCI techniques. In
this paper we present a comprehensive framework to address this
issue. Our evaluation of a computer vision application shows that in
addition to the accuracy, it is vital to address human factors
Abstract: In modern human computer interaction systems
(HCI), emotion recognition is becoming an imperative characteristic.
The quest for effective and reliable emotion recognition in HCI has
resulted in a need for better face detection, feature extraction and
classification. In this paper we present results of feature space analysis
after briefly explaining our fully automatic vision based emotion
recognition method. We demonstrate the compactness of the feature
space and show how the 2d/3d based method achieves superior features
for the purpose of emotion classification. Also it is exposed that
through feature normalization a widely person independent feature
space is created. As a consequence, the classifier architecture has
only a minor influence on the classification result. This is particularly
elucidated with the help of confusion matrices. For this purpose
advanced classification algorithms, such as Support Vector Machines
and Artificial Neural Networks are employed, as well as the simple k-
Nearest Neighbor classifier.
Abstract: Human Computer Interaction (HCI) has been an
emerging field that draws in the experts from various fields to
enhance the application of computer programs and the ease of
computer users. HCI has much to do with learning and cognition and
an emerging approach to learning and problem-solving is problembased
learning (PBL). The processes of PBL involve important
cognitive functions in the various stages. This paper will illustrate
how closely related fields to HCI, PBL and cognitive psychology can
benefit from informing each other through analysing various
cognitive functions. Several cognitive functions from cognitive
function disc (CFD) would be presented and discussed in relation to
human-computer interface. This paper concludes with the
implications of bridging the gaps amongst these disciplines.
Abstract: The paper presents a novel idea to control computer
mouse cursor movement with human eyes. In this paper, a working
of the product has been described as to how it helps the special
people share their knowledge with the world. Number of traditional
techniques such as Head and Eye Movement Tracking Systems etc.
exist for cursor control by making use of image processing in which
light is the primary source. Electro-oculography (EOG) is a new
technology to sense eye signals with which the mouse cursor can be
controlled. The signals captured using sensors, are first amplified,
then noise is removed and then digitized, before being transferred to
PC for software interfacing.
Abstract: Facial expression analysis is rapidly becoming an
area of intense interest in computer science and human-computer
interaction design communities. The most expressive way humans
display emotions is through facial expressions. In this paper we
present a method to analyze facial expression from images by
applying Gabor wavelet transform (GWT) and Discrete Cosine
Transform (DCT) on face images. Radial Basis Function (RBF)
Network is used to classify the facial expressions. As a second stage,
the images are preprocessed to enhance the edge details and non
uniform down sampling is done to reduce the computational
complexity and processing time. Our method reliably works even
with faces, which carry heavy expressions.
Abstract: Hand gesture is an active area of research in the vision
community, mainly for the purpose of sign language recognition and
Human Computer Interaction. In this paper, we propose a system to
recognize alphabet characters (A-Z) and numbers (0-9) in real-time
from stereo color image sequences using Hidden Markov Models
(HMMs). Our system is based on three main stages; automatic segmentation
and preprocessing of the hand regions, feature extraction
and classification. In automatic segmentation and preprocessing stage,
color and 3D depth map are used to detect hands where the hand
trajectory will take place in further step using Mean-shift algorithm
and Kalman filter. In the feature extraction stage, 3D combined features
of location, orientation and velocity with respected to Cartesian
systems are used. And then, k-means clustering is employed for
HMMs codeword. The final stage so-called classification, Baum-
Welch algorithm is used to do a full train for HMMs parameters.
The gesture of alphabets and numbers is recognized using Left-Right
Banded model in conjunction with Viterbi algorithm. Experimental
results demonstrate that, our system can successfully recognize hand
gestures with 98.33% recognition rate.
Abstract: Increase in using internet makes some problems that
one of them is "internet anxiety". Internet anxiety is a type of anxious
that people may feel during surfing internet or using internet for their
educational purpose, blogging or streaming to digital libraries. The
goal of this study is evaluating of internet anxiety among the
management students. In this research Ealy's internet anxiety
questionnaire, consists of positive and negative items, is completed
by 310 participants. According to the findings, about 64.7% of them
were equal or below to mean anxiety score (50). The distribution of
internet anxiety scores was normal and there was no meaningful
difference between men-s and women's anxiety level in this sample.
Results also showed that there is no meaningful difference of internet
anxiety level between different fields of study in Management. This
evaluation will help managers to perform gap analysis between the
existent level and the desired one. Future work would be providing
techniques for abating human anxiety while using internet via human
computer interaction techniques.