Preface - kmutt

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MOVIE CLIPS USING MOVEMENT AND
PACE FEATURES
Saowaluk Watanapa, Bundit Thipakorn,
Nipon Charoenkitkarn
The 5 th IASTED International Conference on
Visualization, Imaging, and Image Processing
(VIIP2005), September 7-9, 2005, Benidorm,
Spain
Classifying multimedia data into
semantic, such as emotional, categories is
challenging and useful. Using two film artistic
components: movement and pace, this paper
proposes a method that can distinguish movie
clips belonging to the excitement class from the
others. Movement is represented by the Average
Squared Motion Vector Magnitude feature, and
pace is represented by the Average Shot
Duration feature. Classification experiments
with 101 data clips, excerpted from 24
Hollywood movies, are conducted, employing
minimum distance and k-NN classifiers. The
results show that the selected features can
potentially separate the excitement movie clips
from the others with above 90% accuracy.
IC-005 SEMANTIC PERSONAL IMAGE
CLASSIFICATION BY ENERGY
EXPENDITURE
Sirinporn Chinpanchana,
Songrit Maneewongvatana, Bundit Thipakorn
International Symposium on Communications
and Information Technologies (ISCIT2005),
October 12-15, 2005, Fragrant Hill Hotel,
Beijing, China, p. 1072
Semantic personal image classification
is an attention problem in multimedia image
retrieval. In our previous work, we classified
semantic images into Business, Leisure, and
Sport categories by integrating the frequency
pattern relationships between body parts and
objects. However, the accuracy mainly depends
on their objects. In the images that have high
semantic complexities, the body movement play
important solve on the meaning of image. In this
paper, we present a new model to achieve
more effective classifier called an Energy
Expenditure model (EE). The EE model is based
on the concept that human subjects in different
classes of images are likely to spend different
amounts of energy. The angular position and
flexion forces are related into each body part.
KMUTT Annual Research Abstracts 2005
Experimental results show that the EE a can
achieve an improvement of semantic images.
IC-006 THE DEVIATION OF GLOTTAL FLOW
DERIVATIVE MODEL DUE TO EMOTIONAL
SPEECH
Suthathip Chuenwattanapranithi,
Songrit Maneewongvatana, Bundit Thipakorn
The 2005 Electrical Engineering/Electronics,
Computer, Telecommunications, and
Information Technology International
Conference (ECTI-CON 2005), May 12-13,
2005, Asia Pattaya Beach Hotel, Pattaya,
Cholburi, Thailand
It is well studied that the changes of the
glottal flow pulse have a direct effect on the
acoustic and perceptual features of an
individual's utterance. These features, in turn,
have influences on perceptual voice qualities of
the phonations which are closely related to the
emotion of the speaker. In this paper, we study
the effects of emotional speech on the shape of
the glottal flow pulse. Specifically, we use LF
model to represent the glottal flow derivative
pulse of emotional speeches. Our hypothesis is
that each emotional speech would have a distinct
shape of the glottal flow derivative pulse
compared to neutral speech. This implies that
parameters of the LF model can be used to
determine the emotion of the speaker. We
perform a set of experiments on several
emotional speech databases, each provides four
emotional states: anger joy, sadness and neutral.
Two-way ANOVA analyses confirm our
hypothesis. The essential LF parameters are
extracted and used for emotional speech
recognition. This feature set achieves high
accuracy on recognizing anger and sadness
emotional speeches.
IC-007 A COMPARISON OF TWO CAMERA
POSE METHODS FOR AUGMENTED
REALITY
Varin Chouvatut, Suthep Madarasmi
The 7 th IASTED International Conference Signal
and Image Processing, August 15-17, 2005,
Honolulu, Hawaii, USA., p. 554
In an augmented reality (AR) system,
also known as mixed reality (MR) system, 3-D
virtual objects can be realistically added into a
real, dynamic, 3-D environment to create an
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