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David C. Levy - One of the best experts on this subject based on the ideXlab platform.
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Source Direction Detection based on Stationary Electronic Nose System
World Academy of Science Engineering and Technology International Journal of Electrical Computer Energetic Electronic and Communication Engineering, 2008Co-Authors: Jie Cai, David C. LevyAbstract:Electronic nose (array of chemical sensors) are widely used in food industry and pollution control. Also it could be used to locate or detect the Direction of the Source of emission odors. Usually this task is performed by electronic nose (ENose) cooperated with mobile vehicles, but when a Source is instantaneous or surrounding is hard for vehicles to reach, problem occurs. Thus a method for stationary ENose to detect the Direction of the Source and locate the Source will be required. A novel method which uses the ratio between the responses of different sensors as a discriminant to determine the Direction of Source in natural wind surroundings is presented in this paper. The result shows that the method is accurate and easily to be implemented. This method could be also used in movably, as an optimized algorithm for robot tracking Source location. Keywords—Electronic nose, Nature wind situation, Source Direction detection.
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Tracking Dynamic Source Direction with a Novel Stationary Electronic Nose System
Sensors, 2006Co-Authors: Jie Cai, David C. LevyAbstract:Abstract: Arrays of chemical sensors, usually called electronic noses (ENose), are widelyused in industry for classifying and identifying odours. They may also be used to locate theposition and detect the Direction of an emission Source. Usually this task is performed by anENose cooperating with a mobile vehicle, but when a Source is instantaneous, or thesurrounding terrain is hard for vehicles to traverse, an alternative approach is needed. Thus athree-step method for a stationary ENose with a novel structure to detect the Direction of adynamic Source is presented in this paper. The method uses the ratio of measuredconcentration from different sensors (C n / C 1 where n=2, 4) as a discriminator. In addition,this method could easily be adapted to robotics as an optimized algorithm for path trackingto a Source location. The paper presents the results of a simulation of the method. Keywords: Electronic nose, Direction detection, Dynamic Source tracking, Nature windsituation 1. Introduction
Jie Cai - One of the best experts on this subject based on the ideXlab platform.
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Source Direction Detection based on Stationary Electronic Nose System
World Academy of Science Engineering and Technology International Journal of Electrical Computer Energetic Electronic and Communication Engineering, 2008Co-Authors: Jie Cai, David C. LevyAbstract:Electronic nose (array of chemical sensors) are widely used in food industry and pollution control. Also it could be used to locate or detect the Direction of the Source of emission odors. Usually this task is performed by electronic nose (ENose) cooperated with mobile vehicles, but when a Source is instantaneous or surrounding is hard for vehicles to reach, problem occurs. Thus a method for stationary ENose to detect the Direction of the Source and locate the Source will be required. A novel method which uses the ratio between the responses of different sensors as a discriminant to determine the Direction of Source in natural wind surroundings is presented in this paper. The result shows that the method is accurate and easily to be implemented. This method could be also used in movably, as an optimized algorithm for robot tracking Source location. Keywords—Electronic nose, Nature wind situation, Source Direction detection.
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Tracking Dynamic Source Direction with a Novel Stationary Electronic Nose System
Sensors, 2006Co-Authors: Jie Cai, David C. LevyAbstract:Abstract: Arrays of chemical sensors, usually called electronic noses (ENose), are widelyused in industry for classifying and identifying odours. They may also be used to locate theposition and detect the Direction of an emission Source. Usually this task is performed by anENose cooperating with a mobile vehicle, but when a Source is instantaneous, or thesurrounding terrain is hard for vehicles to traverse, an alternative approach is needed. Thus athree-step method for a stationary ENose with a novel structure to detect the Direction of adynamic Source is presented in this paper. The method uses the ratio of measuredconcentration from different sensors (C n / C 1 where n=2, 4) as a discriminator. In addition,this method could easily be adapted to robotics as an optimized algorithm for path trackingto a Source location. The paper presents the results of a simulation of the method. Keywords: Electronic nose, Direction detection, Dynamic Source tracking, Nature windsituation 1. Introduction
Daniel Gibbins - One of the best experts on this subject based on the ideXlab platform.
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Can the Sun's Direction be Estimated from an Image Prior to the Computation of Object Shape?
Journal of Mathematical Imaging and Vision, 1997Co-Authors: Wojciech Chojnacki, Michael J. Brooks, Daniel GibbinsAbstract:Various computational techniques have been developed that performreasonably well in inferring shape from shading. However, thesetechniques typically require substantial prerequisite information ifthey are to evolve an estimate of surface shape. It is thereforeinteresting to consider how depth might be inferred from shadinginformation without prior knowledge of various scene conditions. Oneapproach has been to undertake a pre-processing step ofestimating the light-Source Direction, thereby providing input tothe computation of shape from shading. In this paper, we presentevidence that a versatile light-Source-Direction estimator isunattainable, and propose that, in the absence of domain-specificknowledge, shape and light-Source Direction should be determined ina coupled manner
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Can the Sun‘s Direction be Estimated from an Image Prior to the Computation of Object Shape?
Journal of Mathematical Imaging and Vision, 1997Co-Authors: Wojciech Chojnacki, Michael J. Brooks, Daniel GibbinsAbstract:Various computational techniques have been developed that perform reasonably well in inferring shape from shading. However, these techniques typically require substantial prerequisite information if they are to evolve an estimate of surface shape. It is therefore interesting to consider how depth might be inferred from shading information without prior knowledge of various scene conditions. One approach has been to undertake a pre-processing step of estimating the light-Source Direction, thereby providing input to the computation of shape from shading. In this paper, we present evidence that a versatile light-Source-Direction estimator is unattainable, and propose that, in the absence of domain-specific knowledge, shape and light-Source Direction should be determined in a coupled manner
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Revisiting Pentland's estimator of light Source Direction
Journal of the Optical Society of America A, 1994Co-Authors: Wojciech Chojnacki, Michael J. Brooks, Daniel GibbinsAbstract:We examine the pioneering method of Pentland [ J. Opt. Soc. Am.72, 448 ( 1982)] for automatically estimating Direction of the “sun” (light Source) from a single image. It is shown that, under the assumptions used in the derivation of the method, the estimate of Source Direction is erroneous. Specifically, it is shown that an image-based expression used in calculating Source Direction diverges to infinity as the density of image points is increased and that the formula involving this expression is therefore incorrect. When the method is implemented, the flaw manifests itself in the undesirable dependence of the estimator on image resolution. Supporting experimental evidence is given for this. An alternative Source-Direction estimator that is free of these drawbacks is proposed.
Ryoichi Takashima - One of the best experts on this subject based on the ideXlab platform.
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Monaural sound-Source-Direction estimation using the acoustic transfer function of a parabolic reflection board.
The Journal of the Acoustical Society of America, 2010Co-Authors: Ryoichi Takashima, Tetsuya Takiguchi, Yasuo ArikiAbstract:This paper presents a sound-Source-Direction estimation method using only a single microphone with a parabolic reflection board. A simple signal-power-based method using a parabolic antenna has been proposed in the radar field. But the signal-power-based method is not effective for finding the Direction of a talking person due to the varying power of the uttered speech signals. In this paper, the sound-Source-Direction estimation method focuses on the acoustic transfer function instead of the signal power. The use of the parabolic reflection board leads to a difference in the acoustic transfer functions of the target Direction and the non-target Directions, where the parabolic reflector and its associated microphone rotate together and observe the speech at each angle. The acoustic transfer function is estimated from the observed speech using the statistics of clean speech signals. Its effectiveness has been confirmed by monaural sound-Source-Direction estimation experiments in a room environment.
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FUSION - Monaural sound-Source-Direction estimation using the acoustic transfer function of an active microphone
2009Co-Authors: Ryoichi Takashima, Tetsuya Takiguchi, Yasuo ArikiAbstract:This paper introduces an active microphone concept that achieves a good combination of active-operation and signal processing, where a new sound-Source-Direction estimation method using only a single microphone with a parabolic reflection board is proposed. A simple signal-power-based method using a parabolic antenna has been proposed in the radar field. But the signal-power-based method is not effective for finding the Direction of a talking person due to the varying power of the uttered speech signals. In this paper, the sound-Source-Direction estimation method focuses on the acoustic transfer function instead of the signal power. The use of the parabolic reflection board leads to a difference in the acoustic transfer functions of the target Direction and the non-target Directions, where the active microphone rotates and observes the speech at each angle. The acoustic transfer function is estimated from the observed speech using the statistics of clean speech signals. Its effectiveness is confirmed by monaural sound-Source-Direction estimation experiments in a room environment.
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Estimation of Sound Source Direction Using Parabolic Reflection Board
2008Co-Authors: Tetsuya Takiguchi, Ryoichi Takashima, Yasuo ArikiAbstract:This paper presents a new sound-Source-Direction estimation method using only a single microphone with a parabolic reflection board. In our previous work [ 1], we proposed GMM (Gaussian Mixture Model) separation for estimation of the sound Source Direction, where the observed (reverberant) speech is separated into the acoustic transfer function and the clean speech GMM. However, the previous method required the measurement of speech for each room environment in advance. The new proposed method using the parabolic reflection is able to estimate the sound Source Direction without any measurement in advance. Its effectiveness is confirmed by sound-Source-Direction estimation experiments in a room environment.
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Active Microphone with Parabolic Reflection Board for Estimation of Sound Source Direction
2008 Hands-Free Speech Communication and Microphone Arrays, 2008Co-Authors: Tetsuya Takiguchi, Ryoichi Takashima, Yasuo ArikiAbstract:This paper introduces a concept of an active microphone that achieves a good combination of active-operation and signal processing, where a new sound-Source-Direction estimation method using only a single microphone with a parabolic reflection board is proposed. In our previous work [1], we proposed GMM (Gaussian Mixture Model) separation for estimation of the sound Source Direction, where the observed (reverberant) speech is separated into the acoustic transfer function and the clean speech GMM. However, the previous method required the measurement of speech for each room environment in advance. The new proposed method using parabolic reflection is able to estimate the sound Source Direction without any prior measurements. Its effectiveness is confirmed by sound-Source-Direction estimation experiments on white noise in a room environment.
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ACTIVEMICROPHONE WITH PARABOLICREFLECTIONBOARD FOR ESTIMATIONOF SOUND Source Direction
2008Co-Authors: Tetsuya Takiguchi, Ryoichi TakashimaAbstract:modelwithout texts oftheuser's utterance, whereaGMM Thispaper introduces aconcept ofanactive microphone that (Gaussian Mixture Model) was used tomodelthefeatures of achieves agoodcombination ofactive-operation andsignaltheclean speech. This estimation is performed inthecepstral processing, whereanewsound-Source-Direction estimation domain employing amaximum-likelihood-based approach. method using onlyasingle microphone withaparabolic re- This ispossible because thecepstral parameters areaneffecflection boardisproposed. Inourprevious work[1], we tive representation toretain useful clean speech information. proposed GMM (Gaussian Mixture Model) separation for es- Theexperiment results ofourtalker-localizat ion showed its timation ofthesound SourceDirection, wheretheobservedeffectiveness. However, theprevious methodrequired the (reverberant) speech isseparated into theacoustic transfermeasurement ofspeech foreachroomenvironment inadfunction andtheclean speech GMM.However, thepreviousvance. Therefore, this paper presents anewmethod that uses method required themeasurement ofspeech foreachroom parabolic reflection that isable toestimate thesound Source environment inadvance. Thenewproposed methodusing Direction without anyneedforprior measurements. parabolic reflection isable toestimate thesoundSource di- Ineveryday life, ifaninteresting sound isalmost inauDirection without anyprior measurements. Itseffectiveness is ble, people usually adjust theangle oftheir ears sothat their confirmed bysound-Source-Direction
Yasuo Ariki - One of the best experts on this subject based on the ideXlab platform.
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Monaural sound-Source-Direction estimation using the acoustic transfer function of a parabolic reflection board.
The Journal of the Acoustical Society of America, 2010Co-Authors: Ryoichi Takashima, Tetsuya Takiguchi, Yasuo ArikiAbstract:This paper presents a sound-Source-Direction estimation method using only a single microphone with a parabolic reflection board. A simple signal-power-based method using a parabolic antenna has been proposed in the radar field. But the signal-power-based method is not effective for finding the Direction of a talking person due to the varying power of the uttered speech signals. In this paper, the sound-Source-Direction estimation method focuses on the acoustic transfer function instead of the signal power. The use of the parabolic reflection board leads to a difference in the acoustic transfer functions of the target Direction and the non-target Directions, where the parabolic reflector and its associated microphone rotate together and observe the speech at each angle. The acoustic transfer function is estimated from the observed speech using the statistics of clean speech signals. Its effectiveness has been confirmed by monaural sound-Source-Direction estimation experiments in a room environment.
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FUSION - Monaural sound-Source-Direction estimation using the acoustic transfer function of an active microphone
2009Co-Authors: Ryoichi Takashima, Tetsuya Takiguchi, Yasuo ArikiAbstract:This paper introduces an active microphone concept that achieves a good combination of active-operation and signal processing, where a new sound-Source-Direction estimation method using only a single microphone with a parabolic reflection board is proposed. A simple signal-power-based method using a parabolic antenna has been proposed in the radar field. But the signal-power-based method is not effective for finding the Direction of a talking person due to the varying power of the uttered speech signals. In this paper, the sound-Source-Direction estimation method focuses on the acoustic transfer function instead of the signal power. The use of the parabolic reflection board leads to a difference in the acoustic transfer functions of the target Direction and the non-target Directions, where the active microphone rotates and observes the speech at each angle. The acoustic transfer function is estimated from the observed speech using the statistics of clean speech signals. Its effectiveness is confirmed by monaural sound-Source-Direction estimation experiments in a room environment.
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Estimation of Sound Source Direction Using Parabolic Reflection Board
2008Co-Authors: Tetsuya Takiguchi, Ryoichi Takashima, Yasuo ArikiAbstract:This paper presents a new sound-Source-Direction estimation method using only a single microphone with a parabolic reflection board. In our previous work [ 1], we proposed GMM (Gaussian Mixture Model) separation for estimation of the sound Source Direction, where the observed (reverberant) speech is separated into the acoustic transfer function and the clean speech GMM. However, the previous method required the measurement of speech for each room environment in advance. The new proposed method using the parabolic reflection is able to estimate the sound Source Direction without any measurement in advance. Its effectiveness is confirmed by sound-Source-Direction estimation experiments in a room environment.
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Active Microphone with Parabolic Reflection Board for Estimation of Sound Source Direction
2008 Hands-Free Speech Communication and Microphone Arrays, 2008Co-Authors: Tetsuya Takiguchi, Ryoichi Takashima, Yasuo ArikiAbstract:This paper introduces a concept of an active microphone that achieves a good combination of active-operation and signal processing, where a new sound-Source-Direction estimation method using only a single microphone with a parabolic reflection board is proposed. In our previous work [1], we proposed GMM (Gaussian Mixture Model) separation for estimation of the sound Source Direction, where the observed (reverberant) speech is separated into the acoustic transfer function and the clean speech GMM. However, the previous method required the measurement of speech for each room environment in advance. The new proposed method using parabolic reflection is able to estimate the sound Source Direction without any prior measurements. Its effectiveness is confirmed by sound-Source-Direction estimation experiments on white noise in a room environment.
