Wireless Sensor Systems (WSN) is a broad, exciting area with new perspectives and growing growth over the past decades, where more research is being done. WSNs contain many (hundreds of thousands) of micro-sized, chea...
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Most existing camera placement algorithms focus on coverage and/or visibility analysis, which ensures that the object of interest is visible in the camera's field of view (FOV). According to recent literature, han...
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Most existing camera placement algorithms focus on coverage and/or visibility analysis, which ensures that the object of interest is visible in the camera's field of view (FOV). According to recent literature, handoff safety margin is introduced to sensor planning so that sufficient overlapped FOVs among adjacent cameras are reserved for successful and smooth target transition. In this paper, we investigate the sensor planning problem when considering the dynamic interactions between moving targets and observing cameras. The probability of camera overload is explored to model the aforementioned interactions. The introduction of the probability of camera overload also considers the limitation that a given camera can simultaneously monitor or track a fixed number of targets and incorporates the target's dynamics into sensor planning. The resulting camera placement not only achieves the optimal balance between coverage and handoff success rate but also maintains the optimal balance in environments with various target densities. The proposed camera placement method is compared with a reference algorithm by Erdem and Sclaroff. Consistently improved handoff success rate is illustrated via experiments using typical office floor plans with various target densities.
The third international conference on Human-Robot Interaction (HRI-2008) was held in Amsterdam, The Netherlands, March 12-15, 2008. The theme of HRI-2008, "living with robots," highlights the importance of t...
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This volume constitutes the thoroughly refereed conference proceedings of the 26th International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2013, held in Amste...
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ISBN:
(数字)9783642385773
ISBN:
(纸本)9783642385766
This volume constitutes the thoroughly refereed conference proceedings of the 26th International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2013, held in Amsterdam, The Netherlands, in June 2013.
The total of 71 papers selected for the proceedings were carefully reviewed and selected from 185 submissions. The papers focus on the following topics: auctions and negotiation, cognitive modeling, crowd behavior modeling, distributed systems and networks, evolutionary algorithms, knowledge representation and reasoning, pattern recognition, planning, problem solving, robotics, text mining, advances in recommender systems, business process intelligence, decision support for safety-related systems, innovations in intelligent computation and applications, intelligent image and signal processing, and machine learning methods applied to manufacturing processes and production systems.
Lifelogging is a process of collecting rich source of information about daily life of people. In this paper, we introduce the problem of sentiment analysis in egocentric events focusing on the moments that compose the...
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Learning motor skills for robots is a hard task. In particular, a high number of degrees-of-freedom in the robot can pose serious challenges to existing reinforcement learning methods, since it leads to a high-dimensi...
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The ability to detect features within confocal microscope images is important for the interpretation and analysis of such data. Most detectors are gradient-based, and so are sensitive to noise, and fail to accurately ...
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Recognizing faces is a difficult problem due to the generally similar shape of faces combined with the considerable variability in images of the same face under different viewing conditions. In this paper we consider ...
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In this paper, we consider the Hamiltonian alternating path problem for graphs, multigraphs, and digraphs. We describe an approach to solve the problem. This approach is based on constructing logical models for the pr...
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In this paper, we consider the Hamiltonian alternating path problem for graphs, multigraphs, and digraphs. We describe an approach to solve the problem. This approach is based on constructing logical models for the problem. We use logical models for the Hamiltonian alternating path problem to solve the Hamiltonian path problem and the planning a typical working day for indoor service robots problem. Also, we use these models for Bennett's model of cytogenetics, automatic generation of recognition modules, and algebraic data.
Arc-annotated sequences are useful in representing the structural information of RNA and protein sequences. In particular, arc-annotated sequences are useful in describing the secondary and tertiary structures of RNA ...
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Arc-annotated sequences are useful in representing the structural information of RNA and protein sequences. In particular, arc-annotated sequences are useful in describing the secondary and tertiary structures of RNA and protein sequences. Structure comparison for RNA and for protein sequences has become a central computational problem bearing many challenging computerscience questions. The longest arc-preserving common subsequence problem has been introduced as a framework for studying the similarity of arc-annotated sequences. It is a sound and meaningful mathematical formalization of comparing the secondary structures of molecular sequences. In this paper, we consider two special cases of the longest arc-preserving common subsequence problem, efragment LAPCS (unlimited, plain), c-fragment LAPCS (unlimited, unlimited). In particular, we consider a parameterized version of the 1-fragment LAPCS (unlimited, plain) problem, parameterized by the length l of the desired subsequence. We show W[1]-completeness of the problem. Also, we describe an approach to solve c-fragment LAPCS (unlimited, unlimited). This approach is based on constructing logical models for the problem.
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