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The pollen grains of different plant taxa exhibit various shapes and sizes. This structural diversity has made the identification and classification of pollen grains an important tool in many fields. Despite the myriad of applications, the classification of pollen grains is still a tedious and time-consuming process that must be performed by highly skilled specialists. In this paper, we propose an...
Spatio-Temporal interest points are the most popular feature representation in the field of action recognition. A variety of methods have been proposed to detect and describe local patches in video with several techniques reporting state of the art performance for action recognition. However, the reported results are obtained under different experimental settings with different datasets, making it...
A significant proportion of Web traffic is now attributed to Web robots, and this proportion is likely to grow over time. These robots may threaten the security, privacy, functionality, and performance of a Web server due to their unregulated crawling behavior. Therefore, to assess their impact, it must be possible to accurately detect Web robot requests. Contemporary detection approaches, however,...
When human exercises multi-degrees of freedom (DOF) motion, they just pay attention to only part of the body motion and can control the whole body motion. By consciously adjusting low-DOF movements, it is possible to induce multi-DOF motion, which is referred as a “knack” in the sport. Acquiring knacks can drastically improve multi-DOF motor skills by low-DOF information presentation, and it is also...
A system for humanoid robot arm movement concerns about generating a human-like point-to-point (p2p) trajectory. For more than a decade, numerous systems have been devised and many of them were based on complex dynamical systems. In this paper, we introduce a simpler system, integrating support vector machine (SVM) learning model, which can achieve same p2p objective. In our experiment, we compare...
Aim to improve upper limb rehabilitation effect, we design and develop an Image-projective Desktop Arm Trainer (IDAT). Compared with conventional therapy, IDAT provides a more effective and interesting training method. IDAT's goal is to maintain and improve patients' upper limb function by training their eye-hand coordination. We select step-on interface (SOI) as the input system which makes trainees...
Human activity recognition finds many applications in areas such as surveillance, and sports. Such a system classifies a spatio-temporal feature descriptor of a human figure in a video, based on training examples. However many classifiers face the constraints of the long training time, and the large size of the feature vector. Our method, due to the use of an Support Vector Machine (SVM) classifier,...
Performing general human behavior by experts' navigation is expected to be realized as wearable and ubiquitous technologies and computing develop further. For example, the user of the behavior navigation system will be able to conduct first aid treatment as an expert would. We proposed and developed the Wearable Behavior Navigation System (WBNS) using Augmented Reality (AR) technology. By using the...
This paper proposes a framework for the design of serious games in the area of revenue management. At this time, there is little systematic consideration of simulation-based serious games and their set-up available in this field. The suggested framework regards games as structured in three layered stages and explicates decisions influencing their design and focus. These decisions are structured according...
In this paper a new method of eye blink detection and analysis is proposed. The described technique is based on a combination of spatial and temporal derivatives calculated in video sequences acquired with a high speed camera. The pixels of each frame are divided into two groups according to the direction and magnitude of the hybrid gradient vectors and the distance between their centers of gravity...
Expressing emotion to others and recognizing emotion state of the counterpart are not difficult for human. Emotion state of a person may be recognized from the facial expression, voice, and/or gesture. Speech emotion recognition research gained a lot of attention in recent years. One of the important subjects in speech emotion recognition research is the feature selection. The speech features used...
In this paper, we discuss the causes and implications of fratricide in a battlespace increasingly governed by information and intelligence. We propose that, by integrating artificial intention awareness into battlefield communication and control systems by means of the Digital Crosstalk client-server architecture, we can address many of the problems that have been found to be causative agents in fratricide...
We address the problem of predicting the miRNA: miRNA∗ duplex stemming from a microRNA (miRNA) hairpin precursor and we present a SVM-based methodology to address it. Predicting the miRNA: miRNA∗ duplex is a first step towards identifying the mature miRNA, suggesting possible miRNA targets and ultimately, reducing experimentation effort, time, and cost. We measure the error in terms of the absolute...
Based on "information complex holographic person" hypothesis, any systems involved to person can be considered a giant complexity intelligent system. The Internet of Things (IoT) can bring Interconnection, Human to Human (H2H), Human to Things (H2T), Things to Things(T2T). So higher education and the Internet of Things should be giant complexity intelligent systems. In essence, the Internet...
We explore the use of manifold learning as a suitable representation for recognizing visual signs found in Filipino Sign Language. During the learning phase, a reference manifold is derived from a training set of visual signs using Isomap, a non-linear manifold learning algorithm. Individual signs are then projected onto this reference manifold transforming them into trajectories which are compiled...
This paper presents hand grasp classifier using perimeter change of the forearm. Two sensors based on strain gauge were employed. Signal processing was applied to remove some ripples. Four different classes were trained. Real time classifier was used to recognize the trained grasps. Experimental results show that the average accuracy was 81.2%.
In order to have a rich representation for human action, we propose to combine two complementary features so that a human posture can be characterized in more details. In particular, the distance signal feature and the width feature are combined in an effective way to enhance each other's discriminating capability. The resulting feature vector is quantized into mid-level features using k-means clustering...
This paper introduces the design of a real time vision-based motion synthesis system. the system requires user to wear the markers in a certain color. Based on that, several novel algorithms were used for feature detection and feature tracking under occlusion by estimating the velocity of missing features based on the prior, smoothness and fitness term. These algorithms ensured the accuracy and low...
Detecting objects in underwater image sequences and video frames automatically, requires the application of selected algorithms in consecutive steps. Most of these algorithms are controlled by a set of parameters, which need to be calibrated for an optimal detection result. Those parameters determine the effectivity and efficiency of an algorithm and their impact is usually well known. There are however...
The recognition of face images is a complicated problem. Face images are often sufferedfrom variations in brightness, head rotation, facial emotions and so on. Besides, amazing abilities of human brain in face recognition in the presence of these variations, contribute to design face recognition systems based on procedure of human brain. Surveying the recognition and perceptual system of human, shows...
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