Abstract: Background subtraction and temporal difference are
often used for moving object detection in video. Both approaches are
computationally simple and easy to be deployed in real-time image
processing. However, while the background subtraction is highly
sensitive to dynamic background and illumination changes, the
temporal difference approach is poor at extracting relevant pixels of
the moving object and at detecting the stopped or slowly moving
objects in the scene. In this paper, we propose a simple moving object
detection scheme based on adaptive background subtraction and
temporal difference exploiting dynamic background updates. The
proposed technique consists of histogram equalization, a linear
combination of background and temporal difference, followed by the
novel frame-based and pixel-based background updating techniques.
Finally, morphological operations are applied to the output images.
Experimental results show that the proposed algorithm can solve the
drawbacks of both background subtraction and temporal difference
methods and can provide better performance than that of each method.
Abstract: The rapid growth of multimedia technology demands
the secure and efficient access to information. This fast growing lose
the confidence of unauthorized duplication. Henceforth the protection
of multimedia content is becoming more important. Watermarking
solves the issue of unlawful copy of advanced data. In this paper,
blind video watermarking technique has been proposed. A luminance
layer of selected frames is interlaced into two even and odd rows of
an image, further it is deinterlaced and equalizes the coefficients of
the two shares. Color watermark is split into different blocks, and the
pieces of block are concealed in one of the share under the wavelet
transform. Stack the two images into a single image by introducing
interlaced even and odd rows in the two shares. Finally, chrominance
bands are concatenated with the watermarked luminance band. The
safeguard level of the secret information is high, and it is
undetectable. Results show that the quality of the video is not
changed also yields the better PSNR values.
Abstract: The new era of digital communication has brought up
many challenges that network operators need to overcome. The high
demand of mobile data rates require improved networks, which is a
challenge for the operators in terms of maintaining the quality of
experience (QoE) for their consumers. In live video transmission,
there is a sheer need for live surveillance of the videos in order to
maintain the quality of the network. For this purpose objective
algorithms are employed to monitor the quality of the videos that are
transmitted over a network. In order to test these objective algorithms,
subjective quality assessment of the streamed videos is required, as the
human eye is the best source of perceptual assessment. In this paper we
have conducted subjective evaluation of videos with varying spatial
and temporal impairments. These videos were impaired with frame
freezing distortions so that the impact of frame freezing on the quality
of experience could be studied. We present subjective Mean Opinion
Score (MOS) for these videos that can be used for fine tuning the
objective algorithms for video quality assessment.
Abstract: UAV’s are small remote operated or automated aerial
surveillance systems without a human pilot aboard. UAV’s generally
finds its use in military and special operation application, a recent
growing trend in UAV’s finds its application in several civil and nonmilitary
works such as inspection of power or pipelines. The
objective of this paper is the augmentation of a UAV in order to
replace the existing expensive sonar (Sound Navigation And
Ranging) based equipment amongst small scale fisherman, for whom
access to sonar equipment are restricted due to limited economic
resources. The surveillance equipment’s present in the UAV will
relay data and GPS (Global Positioning System) location onto a
receiver on the fishing boat using RF signals, using which the
location of the schools of fishes can be found. In addition to this, an
emergency beacon system is present for rescue operations and drone
recovery.
Abstract: Surf is an increasingly popular sport and its performance evaluation is often qualitative. This work aims at using a smartphone to collect and analyze the GPS and inertial sensors data in order to obtain quantitative metrics of the surfing performance. Two approaches are compared for detection of wave rides, computing the number of waves rode in a surfing session, the starting time of each wave and its duration. The first approach is based on computing the velocity from the Global Positioning System (GPS) signal and finding the velocity thresholds that allow identifying the start and end of each wave ride. The second approach adds information from the Inertial Measurement Unit (IMU) of the smartphone, to the velocity thresholds obtained from the GPS unit, to determine the start and end of each wave ride. The two methods were evaluated using GPS and IMU data from two surfing sessions and validated with similar metrics extracted from video data collected from the beach. The second method, combining GPS and IMU data, was found to be more accurate in determining the number of waves, start time and duration. This paper shows that it is feasible to use smartphones for quantification of performance metrics during surfing. In particular, detection of the waves rode and their duration can be accurately determined using the smartphone GPS and IMU.
Abstract: Advance in techniques of image and video processing has enabled the development of intelligent video surveillance systems. This study was aimed to automatically detect moving human objects and to analyze events of dual human interaction in a surveillance scene. Our system was developed in four major steps: image preprocessing, human object detection, human object tracking, and motion trajectory analysis. The adaptive background subtraction and image processing techniques were used to detect and track moving human objects. To solve the occlusion problem during the interaction, the Kalman filter was used to retain a complete trajectory for each human object. Finally, the motion trajectory analysis was developed to distinguish between the interaction and non-interaction events based on derivatives of trajectories related to the speed of the moving objects. Using a database of 60 video sequences, our system could achieve the classification accuracy of 80% in interaction events and 95% in non-interaction events, respectively. In summary, we have explored the idea to investigate a system for the automatic classification of events for interaction and non-interaction events using surveillance cameras. Ultimately, this system could be incorporated in an intelligent surveillance system for the detection and/or classification of abnormal or criminal events (e.g., theft, snatch, fighting, etc.).
Abstract: To explore how the brain may recognise objects in its
general,accurate and energy-efficient manner, this paper proposes the
use of a neuromorphic hardware system formed from a Dynamic
Video Sensor (DVS) silicon retina in concert with the SpiNNaker
real-time Spiking Neural Network (SNN) simulator. As a first step
in the exploration on this platform a recognition system for dynamic
hand postures is developed, enabling the study of the methods used
in the visual pathways of the brain. Inspired by the behaviours of
the primary visual cortex, Convolutional Neural Networks (CNNs)
are modelled using both linear perceptrons and spiking Leaky
Integrate-and-Fire (LIF) neurons.
In this study’s largest configuration using these approaches, a
network of 74,210 neurons and 15,216,512 synapses is created and
operated in real-time using 290 SpiNNaker processor cores in parallel
and with 93.0% accuracy. A smaller network using only 1/10th of the
resources is also created, again operating in real-time, and it is able
to recognise the postures with an accuracy of around 86.4% - only
6.6% lower than the much larger system. The recognition rate of the
smaller network developed on this neuromorphic system is sufficient
for a successful hand posture recognition system, and demonstrates
a much improved cost to performance trade-off in its approach.
Abstract: This paper introduces a video sharing platform based
on WiFi, which consists of camera, mobile phone and PC server. This
platform can receive wireless signal from the camera and show the live
video on the mobile phone captured by camera. In addition, it is able to
send commands to camera and control the camera’s holder to rotate.
The platform can be applied to interactive teaching and dangerous
area’s monitoring and so on. Testing results show that the platform can
share the live video of mobile phone. Furthermore, if the system’s PC
server and the camera and many mobile phones are connected
together, it can transfer photos concurrently.
Abstract: Driver fatigue is an important factor in the increasing
number of road accidents. Dynamic template matching method was
proposed to address the problem of real-time driver fatigue detection
system based on eye-tracking. An effective vision based approach
was used to analyze the driver’s eye state to detect fatigue. The driver
fatigue system consists of Face detection, Eye detection, Eye
tracking, and Fatigue detection. Initially frames are captured from a
color video in a car dashboard and transformed from RGB into YCbCr
color space to detect the driver’s face. Canny edge operator was used
to estimating the eye region and the locations of eyes are extracted.
The extracted eyes were considered as a template matching for eye
tracking. Edge Map Overlapping (EMO) and Edge Pixel Count
(EPC) matching function were used for eye tracking which is used to
improve the matching accuracy. The pixel of eyeball was tracked
from the eye regions which are used to determine the fatigue state of
the driver.
Abstract: Quantitative analyses of whisker movements provide a
means to study functional recovery and regeneration of mouse facial
nerve after an injury. However, accurate tracking of the mouse whisker
movement is challenging. Most methods for whisker tracking require
manual intervention, e.g. fixing the head of the mouse during a study.
Here we describe a semi-automated image processing method, which
is applied to high-speed video recordings of free-moving mice to track
the whisker movements. We first track the head movement of a mouse
by delineating the lower head contour frame-by-frame that allows for
detection of the location and orientation of the head. Then, a region of
interest is identified for each frame; the subsequent application of a
mask and the Hough transform detects the selected whiskers on each
side of the head. Our approach is used to examine the functional
recovery of damaged facial nerves in mice over a course of 21 days.
Abstract: OPEN_EmoRec_II is an open multimodal corpus with
experimentally induced emotions. In the first half of the experiment,
emotions were induced with standardized picture material and in the
second half during a human-computer interaction (HCI), realized
with a wizard-of-oz design. The induced emotions are based on the
dimensional theory of emotions (valence, arousal and dominance).
These emotional sequences - recorded with multimodal data (facial
reactions, speech, audio and physiological reactions) during a
naturalistic-like HCI-environment one can improve classification
methods on a multimodal level.
This database is the result of an HCI-experiment, for which 30
subjects in total agreed to a publication of their data including the
video material for research purposes*. The now available open
corpus contains sensory signal of: video, audio, physiology (SCL,
respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus
Major) and facial reactions annotations.
Abstract: OPEN_EmoRec_II is an open multimodal corpus with
experimentally induced emotions. In the first half of the experiment,
emotions were induced with standardized picture material and in the
second half during a human-computer interaction (HCI), realized
with a wizard-of-oz design. The induced emotions are based on the
dimensional theory of emotions (valence, arousal and dominance).
These emotional sequences - recorded with multimodal data (facial
reactions, speech, audio and physiological reactions) during a
naturalistic-like HCI-environment one can improve classification
methods on a multimodal level.
This database is the result of an HCI-experiment, for which 30
subjects in total agreed to a publication of their data including the
video material for research purposes*. The now available open
corpus contains sensory signal of: video, audio, physiology (SCL,
respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus
Major) and facial reactions annotations.
Abstract: Present study is carried out on six lane divided urban
arterial road in Patna and Pune city of India. Both the road having
distinct differences in terms of the vehicle composition and the road
side parking. Arterial road in Patan city has 33% of non-motorized
mode, whereas Pune arterial road dominated by 65% of Two wheeler.
Also road side parking is observed in Patna city. The field studies
using videography techniques are carried out for traffic data
collection. Data are extracted for one minute duration for vehicle
composition, speed variation and flow rate on selected arterial road of
the two cities. Speed flow relationship is developed and capacity is
determine. Equivalency factor in terms of dynamic car unit is
determine to represent the vehicle is single unit. The variation in the
capacity due to side friction, presence of non motorized traffic and
effective utilization of lane width is compared at concluding remarks.
Abstract: The aim of this paper is to understand emerging
learning conditions, when a visual analytics is implemented and used
in K 12 (education). To date, little attention has been paid to the role
visual analytics (digital media and technology that highlight visual
data communication in order to support analytical tasks) can play in
education, and to the extent to which these tools can process
actionable data for young students. This study was conducted in three
public K 12 schools, in four social science classes with students aged
10 to 13 years, over a period of two to four weeks at each school.
Empirical data were generated using video observations and analyzed
with help of metaphors within Actor-network theory (ANT). The
learning conditions are found to be distinguished by broad
complexity, characterized by four dimensions. These emerge from
the actors’ deeply intertwined relations in the activities. The paper
argues in relation to the found dimensions that novel approaches to
teaching and learning could benefit students’ knowledge building as
they work with visual analytics, analyzing visualized data.
Abstract: The value co-creation has gained much attention in
sales research, but less is known about how salespeople and
customers interact in the authentic business to business (B2B) sales
meetings. The study presented in this paper empirically contributes to
existing research by presenting authentic B2B sales meetings that
were video recorded and analyzed using observation and qualitative
content analysis methods. This paper aims to study key elements of
successful sales interactions between salespeople and customers/
buyers. This study points out that salespeople are selling value rather
than the products or services themselves, which are only enablers in
realizing business benefits. Therefore, our findings suggest that
promoting and easing open discourse is an essential part of a
successful sales encounter. A better understanding of how
salespeople and customers successfully interact would help
salespeople to develop their interpersonal sales skills.
Abstract: Nowadays, huge amount of multimedia repositories
make the browsing, retrieval and delivery of video contents very slow
and even difficult tasks. Video summarization has been proposed to
improve faster browsing of large video collections and more efficient
content indexing and access. In this paper, we focus on approaches to
video summarization. The video summaries can be generated in many
different forms. However, two fundamentals ways to generate
summaries are static and dynamic. We present different techniques
for each mode in the literature and describe some features used for
generating video summaries. We conclude with perspective for
further research.
Abstract: The detection of moving objects from a video image
sequences is very important for object tracking, activity recognition,
and behavior understanding in video surveillance.
The most used approach for moving objects detection / tracking is
background subtraction algorithms. Many approaches have been
suggested for background subtraction. But, these are illumination
change sensitive and the solutions proposed to bypass this problem
are time consuming.
In this paper, we propose a robust yet computationally efficient
background subtraction approach and, mainly, focus on the ability to
detect moving objects on dynamic scenes, for possible applications in
complex and restricted access areas monitoring, where moving and
motionless persons must be reliably detected. It consists of three
main phases, establishing illumination changes invariance,
background/foreground modeling and morphological analysis for
noise removing.
We handle illumination changes using Contrast Limited Histogram
Equalization (CLAHE), which limits the intensity of each pixel to
user determined maximum. Thus, it mitigates the degradation due to
scene illumination changes and improves the visibility of the video
signal. Initially, the background and foreground images are extracted
from the video sequence. Then, the background and foreground
images are separately enhanced by applying CLAHE.
In order to form multi-modal backgrounds we model each channel
of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture
Model (GMM). Finally, we post process the resulting binary
foreground mask using morphological erosion and dilation
transformations to remove possible noise.
For experimental test, we used a standard dataset to challenge the
efficiency and accuracy of the proposed method on a diverse set of
dynamic scenes.
Abstract: Since the initial creation of the Barbie doll in 1959, it
became a symbol of US society. Likewise, the Licca-chan, a Japanese
doll created in 1967, also became a Japanese symbolic doll of Japanese
society. Prior to the introduction of Licca-chan, Barbie was already
marketed in Japan but their sales were dismal. Licca-chan (an actual
name: Kayama Licca) is a plastic doll with a variety of sizes ranging
from 21.0 cm to 29.0 cm which many Japanese girls dream of having.
For over 35 years, the manufacturer, Takara Co., Ltd. has sold over 48
million dolls and has produced doll houses, accessories, clothes, and
Licca-chan video games for the Nintendo DS. Many First-generation
Licca-chan consumers still are enamored with Licca-chan, and go to
Licca-chan House, in an amusement park with their daughters. These
people are called Licca-chan maniacs, as they enjoy touring the
Licca-chan’s factory in Tohoku or purchase various Licca-chan
accessories. After the successful launch of Licca-chan into the
Japanese market, a mixed-like doll from the US and Japan, a doll,
JeNny, was later sold in the same Japanese market by Takara Co., Ltd.
in 1982.
Comparison of these cultural iconic dolls, Barbie and Licca-chan,
are analyzed in this paper. In fact, these dolls have concepts of girls’
dreams. By using concepts of mythology of Jean Baudrillard, these
dolls can be represented idealized images of figures in the products for
consumers, but at the same time, consumers can see products with
different perspectives, which can cause controversy.
Abstract: The purpose of this study is to investigate the kinematic
characteristics and differences of the snatch barbell trajectory of 53 kg
class female weight lifters. We take the 2014 Taiwan College Cup
players as examples, and tend to make kinematic applications through
the proven weightlifting barbell track system. The competition videos
are taken by consumer camcorder with a tripod which set up at the side
of the lifter. The results will be discussed in three parts, the first part is
various lifting phase, the second part is the compare lifting between
success and unsuccessful, and the third part is to compare the
outstanding player with the general. Conclusion through the barbell
can be used to observe the trajectories of our players lifting the usual
process cannot be observed in the presence of malfunction or habits, so
that the coach can find the problem and guide the players more
accurately. Our system can be applied in practice and competition to
increase the resilience of the lifter on the field.
Abstract: Learning Management System (LMS) is the system
which uses to manage the learning in order to grouping the content
and learning activity between the lecturer and learner including
online examination and evaluation. Nowadays, it is the borderless
learning era so the learning activities can be accessed from
everywhere in the world and also anytime via the information
technology and media. The learner can easily access to the
knowledge so the different in time and distance is not a constraint for
learning anymore.
The learning pattern which was used in this research is the
integration of the in-class learning and online learning via internet
and will be able to monitor the progress by the Learning management
system which will create the fast response and accessible learning
process via the social media. In order to increase the capability and
freedom of the learner, the system can show the current and history
of the learning document, video conference and also has the chat
room for the learner and lecturer to interact to each other.
So the objectives of the “The Design and Applied of Learning
Management System via Social Media on Internet: Case Study of
Operating System for Business Subject” are to expand the
opportunity of learning and to increase the efficiency of learning as
well as increase the communication channel between lecturer and
student. The data of this research was collect from 30 users of the
system which are students who enroll in the subject. And the result of
the research is in the “Very Good” which is conformed to the
hypothesis.