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We have developed techniques to automatically generate personalised biomechanical models of patients' hearts based on 3D cardiac images. We demonstrate this approach using multi-slice computed tomography images. Unsupervised segmentation was performed using non-rigid image registration with a segmented image. A finite element model was automatically fitted to the segmented data of the left ventricle...
A large number of studies have been reported on top-down influences of visual attention. However, less progress have been made in understanding and modeling its mechanisms in real-world tasks. In this paper, we propose an approach for learning spatial attention taking into account influences of physical actions on top-down attention. For this purpose, we focus on interactive visual environments (video...
The Cave Automated Virtual Environment (CAVE) is being used and investigated by several scientists and researchers from different fields. Using the currently available tools to create and modify simulation scenarios to be rendered inside the CAVE requires users with special programming skills and experiences. Also, current CAVEs do not provide the ability for more than two participants to collaboratively...
The aim of this work is to propose a cloud computing architecture simulation platform for social human-robot interaction. This paper explains the design and development of this system named SIGVerse in four main components, namely (1) SIGServer as the central server, (2) Agent Controller for user applications, (3) Service Provider, and (4) SIGViewer as the client terminal, and web based development...
Cloud Computing allows the use of information technology based on the on-demand utility. This technology can provide benefits to small and medium enterprises with limited capital, human resources, and access to marketing network. A survey conducted on SMEs in the district of Coblong Bandung to dig up the IT needs and analyze their readiness to adopt cloud computing technologies. The survey results...
Agent-based evacuation modeling approach is gained more and more attention for investigating human cognitive capabilities and social behaviors in building fires. This paper mainly overviews the research about various agent-based evacuation models. For the decision-making reflects the intelligence of agent individual, we define three types of behavior decision-making models for agent individual based...
Pedestrian detection is one of the fundamental tasks of an intelligent transportation system. Differences in illumination, posture and point of view make pedestrian detection confront with great challenges. In this paper, we focus on the main defect in the existing methods: the interference of the non-person area. Firstly, we use mapping vectors to map the original feature matrix to the different...
Increasing air-traffic demand implies that new air-traffic management (ATM) concepts lowering controller loads, maintaining safety and increasing efficiency need to be designed and implemented. Many of such ideas are prepared within NextGEN. Before they are deployed to real daily usage in National Airspace System (NAS), they must be rigorously evaluated under realistic conditions. The paper presents...
Automation of aeronautical procedures and automated support tools for controllers and pilots have to be evaluated carefully with human operators in the loop. However, the integration of different vendor's operational aeronautical software applications with experimental support tools in simulated air-space environments is demanding and costly. Existing tools are usually not designed to be integrated...
Multimedia services have become a dominant part of the network and content provider's service portfolio. A formal modeling methodology for video quality assessment not only affords the providers a clear cause-effect management view of their services, but also helps to guide management and planning operations. We examine the relation between network performance and perceived video quality through VIDAR,...
Human identification at a distance has recently gained growing interest from computer vision researchers. This paper presents an automatic gait recognition system that recognizes a person by the way they walk. The gait signature is obtained based on the angle and the contour of the silhouette. For each image sequence, background subtraction is used to extract moving silhouettes of the walker. The...
An extensive amount of research is being undertaken to gracefully solve the Human action recognition problem. To this end, in this paper, we introduce the application of self- similarity surfaces for human action recognition. These surfaces were introduced by Shechtman & Irani (CVPR'07) in the context of matching similarities between images or videos. These surfaces are obtained by matching a...
Orderly and efficient evacuations are the key in saving lives and are of considerable interest to homeland security. There has been a considerable interest in simulation of intelligent agent behavior in the context of agent based modeling. This paper combines Genetic Algorithm (GA) with Neural Networks (NN) to explore how intelligent agents can look for exits during an evacuation. The agents have...
We have built Sim Student, a computational model of learning, and applied it as a peer learner that allows students to learn by teaching. Using Sim Student, we study the effect of tutor learning. In this paper, we discuss an empirical classroom study where we evaluated whether asking students to provide explanations for their tutoring activities facilitates tutor learning -- the self-explanation effect...
A major challenge for Arabic Large Vocabulary Continuous Speech Recognition (LVCSR) is the rich morphology of Arabic, which leads to high Out-of-vocabulary (OOV) rates, and poor Language Model (LM) probabilities. In such cases, the use of morphemes rather than full-words is considered a better choice for LMs. Thereby, higher lexical coverage and less LM perplexities are achieved. On the other side,...
Document summarization algorithms are most commonly evaluated according to the intrinsic quality of the summaries they produce. An alternate approach is to examine the extrinsic utility of a summary, measured by the ability of the summary to aid a human in the completion of a specific task. In this paper, we use topic identification as a proxy for relevancy determination in the context of an information...
Based on “ground truth” eye-tracking data, earlier research [1] shows that adding natural scene saliency (NSS) can improve an objective metric's performance in predicting perceived image quality. To include NSS in a real-world implementation of an objective metric, a computational model instead of eye-tracking data is needed. Existing models of visual saliency are generally designed for a specific...
In data-driven spoken dialog system development, developers should prepare a dialog corpus with semantic annotation. However, the labeling process is a laborious and time consuming task. To reduce human efforts, we propose an unsupervised approach based on non-parametric Bayesian Hidden Markov Model to the problem of modeling user actions. With the non-parametric model, system designers do not need...
This paper is concerned with combining models for decoding an optimum translation for a dictation based machine aided human translation (MAHT) task. Statistical language model (SLM) probabilities in automatic speech recognition (ASR) are updated using statistical machine translation (SMT) model probabilities. The effect of this procedure is evaluated for utterances from human translators dictating...
Recent advances in technologies for capturing video data have opened a vast amount of new application areas. Among them, the incorporation of Time-of-Flight (ToF) cameras on Ambient Intelligence (AmI) environments. Although the performance of tracking algorithms have quickly improved, symbolic models used to represent the resulting knowledge have not yet been adapted for smart environments. This paper...
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