The Experts below are selected from a list of 18966 Experts worldwide ranked by ideXlab platform
Karl Heinz Hoffmann - One of the best experts on this subject based on the ideXlab platform.
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prediction of driver Intended Path at intersections
Intelligent Vehicles Symposium, 2014Co-Authors: Thomas Streubel, Karl Heinz HoffmannAbstract:The complexity of situations occurring at intersections is demanding on the cognitive abilities of drivers. Advanced Driver Assistance Systems (ADAS) are Intended to assist particularly in those situations. However, for adequate system reaction strategies it is essential to develop situation assessment. Especially the driver's intention has to be estimated. So, the criticality can be inferred and efficient intervention strategies can take action. In this paper, we present a prediction framework based on Hidden Markov Models (HMMs) and analyze its performance using a large database of real driving data. Our focus is on the variation of the model parameters and the choice of the dataset for learning. The direction of travel while approaching a 4-way intersection is to be estimated. A solid prediction is accomplished with high prediction rates above 90% and mean prediction times up to 7 seconds before entering the intersection area.
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prediction of driver Intended Path at intersections
Intelligent Vehicles Symposium, 2014Co-Authors: Thomas Streubel, Karl Heinz HoffmannAbstract:The complexity of situations occurring at intersections is demanding on the cognitive abilities of drivers. Advanced Driver Assistance Systems (ADAS) are Intended to assist particularly in those situations. However, for adequate system reaction strategies it is essential to develop situation assessment. Especially the driver's intention has to be estimated. So, the criticality can be inferred and efficient intervention strategies can take action. In this paper, we present a prediction framework based on Hidden Markov Models (HMMs) and analyze its performance using a large database of real driving data. Our focus is on the variation of the model parameters and the choice of the dataset for learning. The direction of travel while approaching a 4-way intersection is to be estimated. A solid prediction is accomplished with high prediction rates above 90% and mean prediction times up to 7 seconds before entering the intersection area.
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Intelligent Vehicles Symposium - Prediction of driver Intended Path at intersections
2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014Co-Authors: Thomas Streubel, Karl Heinz HoffmannAbstract:The complexity of situations occurring at intersections is demanding on the cognitive abilities of drivers. Advanced Driver Assistance Systems (ADAS) are Intended to assist particularly in those situations. However, for adequate system reaction strategies it is essential to develop situation assessment. Especially the driver's intention has to be estimated. So, the criticality can be inferred and efficient intervention strategies can take action. In this paper, we present a prediction framework based on Hidden Markov Models (HMMs) and analyze its performance using a large database of real driving data. Our focus is on the variation of the model parameters and the choice of the dataset for learning. The direction of travel while approaching a 4-way intersection is to be estimated. A solid prediction is accomplished with high prediction rates above 90% and mean prediction times up to 7 seconds before entering the intersection area.
Alfonso Rodriguez-molares - One of the best experts on this subject based on the ideXlab platform.
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Studying the Origin of Reverberation Clutter in Echocardiography: In Vitro Experiments and In Vivo Demonstrations.
Ultrasound in medicine & biology, 2019Co-Authors: Ali Fatemi, Erik Andreas Rye Berg, Alfonso Rodriguez-molaresAbstract:Abstract Clutter in echocardiography hinders the visualization of the heart and reduces the diagnostic value of the images. The detailed mechanisms that generate clutter are, however, not well understood. We present five different hypotheses for generation of clutter based on reverberation artifact with a focus on apical four-chamber view echocardiograms. We demonstrate the plausibility of our hypotheses by in vitro experiments and by comparing the results with in vivo recordings from four volunteers. The results show that clutter in echocardiography can be originated both at structures that lie in the ultrasound beam Path and at those that are outside the imaging plane. We show that reverberations from echogenic structures outside the imaging plane can make clutter over the image if the ultrasound beam gets deflected out of its Intended Path by specular reflection at the ribs. Different clutter types in the in vivo examples show that the appearance of clutter varies, depending on the tissue from which it originates. The results of this work can be applied to improve clutter reduction techniques or to design ultrasound transducers that give higher quality cardiac images. The results can also help cardiologists have a better understanding of clutter in echocardiograms and acquire better images based on the type and the source of the clutter.
Jiandong Li - One of the best experts on this subject based on the ideXlab platform.
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Hop-by-Hop Routing in Wireless Mesh Networks with Bandwidth Guarantees
IEEE Transactions on Mobile Computing, 2012Co-Authors: Ronghui Hou, King-shan Lui, Fred Baker, Jiandong LiAbstract:Wireless Mesh Network (WMN) has become an important edge network to provide Internet access to remote areas and wireless connections in a metropolitan scale. In this paper, we study the problem of identifying the maximum available bandwidth Path, a fundamental issue in supporting quality-of-service in WMNs. Due to interference among links, bandwidth, a well-known bottleneck metric in wired networks, is neither concave nor additive in wireless networks. We propose a new Path weight which captures the available Path bandwidth information. We formally prove that our hop-by-hop routing protocol based on the new Path weight satisfies the consistency and loop-freeness requirements. The consistency property guarantees that each node makes a proper packet forwarding decision, so that a data packet does traverse over the Intended Path. Our extensive simulation experiments also show that our proposed Path weight outperforms existing Path metrics in identifying high-throughput Paths.
Thomas Streubel - One of the best experts on this subject based on the ideXlab platform.
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prediction of driver Intended Path at intersections
Intelligent Vehicles Symposium, 2014Co-Authors: Thomas Streubel, Karl Heinz HoffmannAbstract:The complexity of situations occurring at intersections is demanding on the cognitive abilities of drivers. Advanced Driver Assistance Systems (ADAS) are Intended to assist particularly in those situations. However, for adequate system reaction strategies it is essential to develop situation assessment. Especially the driver's intention has to be estimated. So, the criticality can be inferred and efficient intervention strategies can take action. In this paper, we present a prediction framework based on Hidden Markov Models (HMMs) and analyze its performance using a large database of real driving data. Our focus is on the variation of the model parameters and the choice of the dataset for learning. The direction of travel while approaching a 4-way intersection is to be estimated. A solid prediction is accomplished with high prediction rates above 90% and mean prediction times up to 7 seconds before entering the intersection area.
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prediction of driver Intended Path at intersections
Intelligent Vehicles Symposium, 2014Co-Authors: Thomas Streubel, Karl Heinz HoffmannAbstract:The complexity of situations occurring at intersections is demanding on the cognitive abilities of drivers. Advanced Driver Assistance Systems (ADAS) are Intended to assist particularly in those situations. However, for adequate system reaction strategies it is essential to develop situation assessment. Especially the driver's intention has to be estimated. So, the criticality can be inferred and efficient intervention strategies can take action. In this paper, we present a prediction framework based on Hidden Markov Models (HMMs) and analyze its performance using a large database of real driving data. Our focus is on the variation of the model parameters and the choice of the dataset for learning. The direction of travel while approaching a 4-way intersection is to be estimated. A solid prediction is accomplished with high prediction rates above 90% and mean prediction times up to 7 seconds before entering the intersection area.
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Intelligent Vehicles Symposium - Prediction of driver Intended Path at intersections
2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014Co-Authors: Thomas Streubel, Karl Heinz HoffmannAbstract:The complexity of situations occurring at intersections is demanding on the cognitive abilities of drivers. Advanced Driver Assistance Systems (ADAS) are Intended to assist particularly in those situations. However, for adequate system reaction strategies it is essential to develop situation assessment. Especially the driver's intention has to be estimated. So, the criticality can be inferred and efficient intervention strategies can take action. In this paper, we present a prediction framework based on Hidden Markov Models (HMMs) and analyze its performance using a large database of real driving data. Our focus is on the variation of the model parameters and the choice of the dataset for learning. The direction of travel while approaching a 4-way intersection is to be estimated. A solid prediction is accomplished with high prediction rates above 90% and mean prediction times up to 7 seconds before entering the intersection area.
Eric Royer - One of the best experts on this subject based on the ideXlab platform.
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Outdoor/Indoor Vision Based Localization for Blind Pedestrian Navigation Assistance
International Journal of Image and Graphics, 2010Co-Authors: Sylvie Treuillet, Eric RoyerAbstract:The most challenging issue of the navigation assistive systems for the visually impaired is the instantaneous and accurate spatial localization of the user. Most of the previous proposed systems are based on GPS sensors. But, low cost versions have clearly insufficient accuracy for pedestrian use. Furthermore, they are confined to outdoor navigation with severe failing in urban area. This paper presents a new approach for localizing a person by using a single body mounted camera and computer vision techniques. Instantaneous accurate localization and heading estimates of the person are computed from images as the trip progresses along a memorised Path. A first portable prototype has been tested for outdoor as well as indoor pedestrian trips. Experimental results demonstrate the effectiveness of the vision based localization: the accuracy around twenty centimetres, allows guiding and keeping the blind in a navigation corridor along the Intended Path. In combination with a suitable guiding interface, such a localization system will propose a convenient assistive navigation for the visually impaired.
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OUTDOOR/INDOOR VISION-BASED LOCALIZATION FOR BLIND PEDESTRIAN NAVIGATION ASSISTANCE
International Journal of Image and Graphics, 2010Co-Authors: Sylvie Treuillet, Eric RoyerAbstract:The most challenging issue facing the navigation assistive systems for the visually impaired is the instantaneous and accurate spatial localization of the user. Most of the previously proposed systems are based on global positioning system (GPS) sensors. However, the accuracy of low-cost versions is insufficient for pedestrian use. Furthermore, GPS-based systems are confined to outdoor navigation and experience severe signal losts in urban areas. This paper presents a new approach for localizing a person by using a single-body-mounted camera and computer vision techniques. Instantaneous accurate localization and heading estimates of the person are computed from images as the user progresses along a memorized Path. A portable prototype has been tested for outdoor as well as indoor pedestrian use. Experimental results demonstrate the effectiveness of the vision-based localization: the accuracy is sufficient for making it possible to guide and maintain the blind person within a navigation corridor less than 1 m wide along the Intended Path. In combination with a suitable guiding interface, such a localization system will be convenient to assist the visually impaired in their everyday movements outdoors as well as indoors.
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Body Mounted Vision System For Visually Impaired Outdoor And Indoor Wayfindind Assistance
2007Co-Authors: Sylvie Treuillet, Eric Royer, Thierry Chateau, Michel Dhome, Jean-marc LavestAbstract:The most challenging issue of the navigation assistive systems for the visually impaired is the instantaneous and accurate spatial localization of the user. Most of the previous proposed systems based on GPS sensors have clearly insufficient accuracy for pedestrian use and are confined to outdoor with severe failing in urban area. This paper presents an interesting alternative localization algorithm using a body mounted single camera. Instantaneous accurate localization and heading estimates of the person are computed from images as the trip progresses along a memorised Path. A first portable prototype has been tested for outdoor as well as indoor pedestrian trips. Experimental results demonstrate the effectiveness of the vision based localization to keep the walker in a navigation corridor less than one meter width along the Intended Path. Future works will investigate multimodal adaptative interface taking account the psychological and ergonomic factors for the blind end-user to design a suitable guiding solution for the blind and visually impaired.
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CVHI - Body Mounted Vision System for Visually Impaired Outdoor and Indoor Wayfinding Assistance.
2007Co-Authors: Sylvie Treuillet, Eric Royer, Thierry Chateau, Michel Dhome, Jean-marc LavestAbstract:The most challenging issue of the navigation assistive systems for the visually impaired is the instantaneous and accurate spatial localization of the user. Most of the previous proposed systems based on GPS sensors have clearly insufficient accuracy for pedestrian use and are confined to outdoor with severe failing in urban area. This paper presents an interesting alternative localization algorithm using a body mounted single camera. Instantaneous accurate localization and heading estimates of the person are computed from images as the trip progresses along a memorised Path. A first portable prototype has been tested for outdoor as well as indoor pedestrian trips. Experimental results demonstrate the effectiveness of the vision based localization to keep the walker in a navigation corridor less than one meter width along the Intended Path. Future works will investigate multimodal adaptative interface taking account the psychological and ergonomic factors for the blind end-user to design a suitable guiding solution for the blind and visually impaired.