Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336476
J. Rebut, G. Toulminet, A. Bensrhair
ARCOS is a French research project for secure driving. It aims at improving road safety and integrates engineering, human and social sciences. This paper presents an algorithm of road obstacles detection and a self-adaptive stereo vision system that have been provided and tested in the framework of the ARCOS project. In order to face with different lighting conditions, a new automatic gain and shutter control of the cameras is proposed. The conclusion of the performance of the whole system are discussed.
{"title":"Road obstacles detection using a self-adaptive stereo vision sensor: a contribution to the ARCOS French project","authors":"J. Rebut, G. Toulminet, A. Bensrhair","doi":"10.1109/IVS.2004.1336476","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336476","url":null,"abstract":"ARCOS is a French research project for secure driving. It aims at improving road safety and integrates engineering, human and social sciences. This paper presents an algorithm of road obstacles detection and a self-adaptive stereo vision system that have been provided and tested in the framework of the ARCOS project. In order to face with different lighting conditions, a new automatic gain and shutter control of the cameras is proposed. The conclusion of the performance of the whole system are discussed.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115229961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336435
E. Deutschl, C. Gasser, A. Niel, J. Werschonig
A new vision based inspection technique for rail surface defects is presented. It replaces visual checks with an automatic inspection system. Colour line-scan cameras and a special image acquisition method- the so called spectral image differencing procedure (SIDP- allow the automatic detection of defects on rail surfaces, like flakes, cracks, grooves or break-offs by means of image processing. The system is already used by a rail manufacturer as inline system, but may also be used on testing vehicles. Practice shows that it produces reliable results even for heavily scaled surfaces, which usually pose serious problems to optical inspection systems due to their irregular texture.
{"title":"Defect detection on rail surfaces by a vision based system","authors":"E. Deutschl, C. Gasser, A. Niel, J. Werschonig","doi":"10.1109/IVS.2004.1336435","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336435","url":null,"abstract":"A new vision based inspection technique for rail surface defects is presented. It replaces visual checks with an automatic inspection system. Colour line-scan cameras and a special image acquisition method- the so called spectral image differencing procedure (SIDP- allow the automatic detection of defects on rail surfaces, like flakes, cracks, grooves or break-offs by means of image processing. The system is already used by a rail manufacturer as inline system, but may also be used on testing vehicles. Practice shows that it produces reliable results even for heavily scaled surfaces, which usually pose serious problems to optical inspection systems due to their irregular texture.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114191228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336470
A. Techmer
Monitoring the lateral and rear lane is required for several car vision applications like a blind-spot detection, an overtake checker, a lane change assistant or a door-opener assistant. For these applications a general motion based approach for object detection and tracking in real-time is presented. The approach requires no camera calibration and does not depend on lane detection or model based object detection.
{"title":"Real time motion analysis for monitoring the rear and lateral road","authors":"A. Techmer","doi":"10.1109/IVS.2004.1336470","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336470","url":null,"abstract":"Monitoring the lateral and rear lane is required for several car vision applications like a blind-spot detection, an overtake checker, a lane change assistant or a door-opener assistant. For these applications a general motion based approach for object detection and tracking in real-time is presented. The approach requires no camera calibration and does not depend on lane detection or model based object detection.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123689973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336448
P. Lombardi, B. Zavidovique
Robustness is a key issue in pedestrian detection for autonomous vehicles. Contextual information, if well exploited, should increase robustness and performance. Specifically, contextual knowledge allows for the integration of algorithms performing well only in specific situations, which would otherwise be excluded from a system designed for the general case. Here, we discuss using context in a vision-based system. Contextual evolution of scene parameters is represented as the hidden process of a Hidden Markov Model. Consequently, a Bayesian framework is adopted for all principal elements, including sensor models for specialised algorithms and sensors observing the current context. Our strategy allows re-use of known algorithms, at the same time enabling context-sensitive developments.
{"title":"A context-dependent vision system for pedestrian detection","authors":"P. Lombardi, B. Zavidovique","doi":"10.1109/IVS.2004.1336448","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336448","url":null,"abstract":"Robustness is a key issue in pedestrian detection for autonomous vehicles. Contextual information, if well exploited, should increase robustness and performance. Specifically, contextual knowledge allows for the integration of algorithms performing well only in specific situations, which would otherwise be excluded from a system designed for the general case. Here, we discuss using context in a vision-based system. Contextual evolution of scene parameters is represented as the hidden process of a Hidden Markov Model. Consequently, a Bayesian framework is adopted for all principal elements, including sensor models for specialised algorithms and sensors observing the current context. Our strategy allows re-use of known algorithms, at the same time enabling context-sensitive developments.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126581088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336431
J. McCall, O. Achler, M. Trivedi
We introduce a new type of intelligent vehicle test-bed that is enabling new research in the field. This new test-bed is designed to capture not just a portion of the vehicle surround, but rather the entire vehicle surround as well as the vehicle interior and vehicle state for extended periods of time. This is accomplished using multiple modalities of sensor systems so that it conform a complete context of the vehicle. This allows new research to be performed in intelligent vehicle algorithm development and allows studies in driver behavior to be performed. We also show results from some of the research being performed using this test-bed.
{"title":"Design of an instrumented vehicle test bed for developing a human centered driver support system","authors":"J. McCall, O. Achler, M. Trivedi","doi":"10.1109/IVS.2004.1336431","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336431","url":null,"abstract":"We introduce a new type of intelligent vehicle test-bed that is enabling new research in the field. This new test-bed is designed to capture not just a portion of the vehicle surround, but rather the entire vehicle surround as well as the vehicle interior and vehicle state for extended periods of time. This is accomplished using multiple modalities of sensor systems so that it conform a complete context of the vehicle. This allows new research to be performed in intelligent vehicle algorithm development and allows studies in driver behavior to be performed. We also show results from some of the research being performed using this test-bed.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":" 28","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114051370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336485
Y. Sakamoto, M. Aoki
We propose a new pedestrian environment recognition method for pedestrian walk at a comparatively narrow street area. Pedestrian road side solid structures are modelled as pictures put on flat walls. In our approach, we use multiple, movable panels for modelling pedestrian walk space area. We adjust an opaque panel to road side solid structures and a map texture on the surface. For small structures such as guardrails, utility poles in the road area, we put these textures on a transparent panel. For estimating the wall position in the image, we use a vertical and horizontal line segment of the walls. We adjust the bottom line of the panel to a line connecting bottom points of vertical line segments of walls. Horizontal line segment of walls are used for constraining a search area. For transparent panel adjusting, we use systematic change in texture elements caused by projection. Our method deals with three types of road shapes, straight roads and intersection (+-shaped roads , T-shaped roads). Experimental results for still images show the effectiveness of the proposed method. It can be applied for a visually impaired system.
{"title":"Street model with multiple movable panels for pedestrian environment analysis","authors":"Y. Sakamoto, M. Aoki","doi":"10.1109/IVS.2004.1336485","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336485","url":null,"abstract":"We propose a new pedestrian environment recognition method for pedestrian walk at a comparatively narrow street area. Pedestrian road side solid structures are modelled as pictures put on flat walls. In our approach, we use multiple, movable panels for modelling pedestrian walk space area. We adjust an opaque panel to road side solid structures and a map texture on the surface. For small structures such as guardrails, utility poles in the road area, we put these textures on a transparent panel. For estimating the wall position in the image, we use a vertical and horizontal line segment of the walls. We adjust the bottom line of the panel to a line connecting bottom points of vertical line segments of walls. Horizontal line segment of walls are used for constraining a search area. For transparent panel adjusting, we use systematic change in texture elements caused by projection. Our method deals with three types of road shapes, straight roads and intersection (+-shaped roads , T-shaped roads). Experimental results for still images show the effectiveness of the proposed method. It can be applied for a visually impaired system.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114681174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336351
Leanne Matuszyk, A. Zelinsky, L. Nilsson, M. Rilbe
This paper presents a stereo panoramic sensor as part of a driver assistance system to monitor driver blind-spots around vehicles. With our system we have generated panoramic disparity maps to reliably estimate range to objects in the surrounding environment. It was also proven that it is possible to apply the /spl nu/-disparity algorithm to panoramic images to successfully segment obstacles, even in the case of extremely noisy data. The stereo system has been evaluated using ground truth data, together with extensive field experiments.
{"title":"Stereo panoramic vision for monitoring vehicle blind-spots","authors":"Leanne Matuszyk, A. Zelinsky, L. Nilsson, M. Rilbe","doi":"10.1109/IVS.2004.1336351","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336351","url":null,"abstract":"This paper presents a stereo panoramic sensor as part of a driver assistance system to monitor driver blind-spots around vehicles. With our system we have generated panoramic disparity maps to reliably estimate range to objects in the surrounding environment. It was also proven that it is possible to apply the /spl nu/-disparity algorithm to panoramic images to successfully segment obstacles, even in the case of extremely noisy data. The stereo system has been evaluated using ground truth data, together with extensive field experiments.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115555790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336500
P. Donato, J. Ureña, M. Mazo, F. Álvarez
The reliable detection of the passage of railway units by certain points of the railway line is very important for a safe circulation. Thus, the system proposed in this work makes the detection with the sensor located next to the railway, without additional electronics in this place. All the electronic process equipment is concentrated in a point that can be far away from the rail. Moreover, the proposed sensor is capable of detecting the sense of circulation. In order to compensate for the attenuation in wires and the external noise, we use a signal codified with Golay complementary sequences.
{"title":"Train wheel detection without electronic equipment near the rail line","authors":"P. Donato, J. Ureña, M. Mazo, F. Álvarez","doi":"10.1109/IVS.2004.1336500","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336500","url":null,"abstract":"The reliable detection of the passage of railway units by certain points of the railway line is very important for a safe circulation. Thus, the system proposed in this work makes the detection with the sensor located next to the railway, without additional electronics in this place. All the electronic process equipment is concentrated in a point that can be far away from the rail. Moreover, the proposed sensor is capable of detecting the sense of circulation. In order to compensate for the attenuation in wires and the external noise, we use a signal codified with Golay complementary sequences.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"102 Suppl 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123372189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336373
V. DeBrunner, M. Ta, Dayong Zhou
Vibration mitigation has become increasingly vital for the current highway bridge system. Since the main source of bridge vibrations comes from heavy trucks passing by, we propose a control system that can be installed on the trucks to help reduce bridges' vibration. The approach is based on the nonlinear black-box model of the truck-bridge interaction.
{"title":"On the design of structural vibration control systems for highway bridges","authors":"V. DeBrunner, M. Ta, Dayong Zhou","doi":"10.1109/IVS.2004.1336373","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336373","url":null,"abstract":"Vibration mitigation has become increasingly vital for the current highway bridge system. Since the main source of bridge vibrations comes from heavy trucks passing by, we propose a control system that can be installed on the trucks to help reduce bridges' vibration. The approach is based on the nonlinear black-box model of the truck-bridge interaction.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129409015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336423
Shiliang Sun, Guoqiang Yu, Changshui Zhang
Short-term traffic flow forecasting is an important problem in the research area of intelligent transportation system. In practical situations, flow data may be incomplete, that is, partially missing or unavailable, where few methods could implement forecasting successfully. A method called Sampling Markov Chain is proposed to deal with this circumstance. In this paper, the traffic flow is modeled as a high order Markov Chain; and the transition probability from one state to the other state is approximated by Gaussian Mixture Model (GMM) whose parameters are estimated with Competitive Expectation Maximum (CEM) algorithm. The incomplete data in forecasting the trend of Markov Chain is represented by enough points sampled using the idea of Monte Carlo integration. Experimental results show that the Sampling Markov Chain method is applicable and effective for short-term traffic flow forecasting in case of incomplete data.
{"title":"Short-term traffic flow forecasting using Sampling Markov Chain method with incomplete data","authors":"Shiliang Sun, Guoqiang Yu, Changshui Zhang","doi":"10.1109/IVS.2004.1336423","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336423","url":null,"abstract":"Short-term traffic flow forecasting is an important problem in the research area of intelligent transportation system. In practical situations, flow data may be incomplete, that is, partially missing or unavailable, where few methods could implement forecasting successfully. A method called Sampling Markov Chain is proposed to deal with this circumstance. In this paper, the traffic flow is modeled as a high order Markov Chain; and the transition probability from one state to the other state is approximated by Gaussian Mixture Model (GMM) whose parameters are estimated with Competitive Expectation Maximum (CEM) algorithm. The incomplete data in forecasting the trend of Markov Chain is represented by enough points sampled using the idea of Monte Carlo integration. Experimental results show that the Sampling Markov Chain method is applicable and effective for short-term traffic flow forecasting in case of incomplete data.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129137212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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