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Author |
Jose Manuel Alvarez; Antonio Lopez |
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Title |
Novel Index for Objective Evaluation of Road Detection Algorithms |
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2008 |
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Intelligent Transportation Systems. 11th International IEEE Conference on, |
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815–820 |
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road detection |
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Beijing (Xina) |
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ITSC |
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ADAS @ adas @ AlL2008 |
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1074 |
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Author |
Jose Manuel Alvarez; Antonio Lopez |
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Title |
Road Detection Based on Illuminant Invariance |
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Journal Article |
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2011 |
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IEEE Transactions on Intelligent Transportation Systems |
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TITS |
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12 |
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1 |
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184-193 |
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road detection |
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Abstract |
By using an onboard camera, it is possible to detect the free road surface ahead of the ego-vehicle. Road detection is of high relevance for autonomous driving, road departure warning, and supporting driver-assistance systems such as vehicle and pedestrian detection. The key for vision-based road detection is the ability to classify image pixels as belonging or not to the road surface. Identifying road pixels is a major challenge due to the intraclass variability caused by lighting conditions. A particularly difficult scenario appears when the road surface has both shadowed and nonshadowed areas. Accordingly, we propose a novel approach to vision-based road detection that is robust to shadows. The novelty of our approach relies on using a shadow-invariant feature space combined with a model-based classifier. The model is built online to improve the adaptability of the algorithm to the current lighting and the presence of other vehicles in the scene. The proposed algorithm works in still images and does not depend on either road shape or temporal restrictions. Quantitative and qualitative experiments on real-world road sequences with heavy traffic and shadows show that the method is robust to shadows and lighting variations. Moreover, the proposed method provides the highest performance when compared with hue-saturation-intensity (HSI)-based algorithms. |
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ADAS @ adas @ AlL2011 |
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1456 |
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Author |
Jaume Amores |
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Title |
Vocabulary-based Approaches for Multiple-Instance Data: a Comparative Study |
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2010 |
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20th International Conference on Pattern Recognition |
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4246–4250 |
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Multiple Instance Learning (MIL) has become a hot topic and many different algorithms have been proposed in the last years. Despite this fact, there is a lack of comparative studies that shed light into the characteristics of the different methods and their behavior in different scenarios. In this paper we provide such an analysis. We include methods from different families, and pay special attention to vocabulary-based approaches, a new family of methods that has not received much attention in the MIL literature. The empirical comparison includes seven databases from four heterogeneous domains, implementations of eight popular MIL methods, and a study of the behavior under synthetic conditions. Based on this analysis, we show that, with an appropriate implementation, vocabulary-based approaches outperform other MIL methods in most of the cases, showing in general a more consistent performance. |
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Istanbul, Turkey |
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1051-4651 |
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978-1-4244-7542-1 |
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ICPR |
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ADAS @ adas @ Amo2010 |
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1295 |
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Jaume Amores; Petia Radeva |
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Title |
Non-rigid Registration of Vessel Structures in IVUS Images |
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Miscellaneous |
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2003 |
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In Pattern Recognition and Image Analysis, Lecture Notes in Computer Science. 2652:45–52 |
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Springer-Verlag |
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ADAS @ adas @ AmR2003 |
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363 |
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Jaume Amores; Petia Radeva |
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Title |
Elastic Matching and Retrieval of IVUS Images Using Contextual Information |
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2003 |
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6th Catalan Conference on Artificial Intelligence (CCIA 2003), 137–148 |
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Palma de Mallorca |
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ADAS @ adas @ AmR2003a |
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364 |
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Jaume Amores; Petia Radeva |
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Registration and retrieval of medical images. Application to IVUS |
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Report |
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2004 |
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CVC Technical Report #77 |
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CVC (UAB) |
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MILAB |
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ADAS @ adas @ AmR2004 |
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513 |
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Jaume Amores; Petia Radeva |
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Title |
Retrieval of IVUS Images Using Contextual Information and Elastic Matching |
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2005 |
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International Journal on Intelligent Systems, 20(5):541–560 (IF: 0.657) |
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ADAS @ adas @ AmR2005a |
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593 |
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Author |
Jaume Amores; Petia Radeva |
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Title |
Registration and Retrieval of Highly Elastic Bodies using Contextual Information |
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2005 |
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Pattern Recognition Letters |
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PRL |
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26 |
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11 |
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1720–1731 |
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IF: 1.138 |
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ADAS @ adas @ AmR2005b |
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592 |
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Author |
Niki Aifanti; Angel Sappa; N. Grammalidis; Sotiris Malassiotis |
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Title |
Human Motion Tracking and Recognition |
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2005 |
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Encyclopedia of Information Science and Technology, 1(5):1355–1360 |
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496 |
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Niki Aifanti; Angel Sappa; N. Grammalidis; Sotiris Malassiotis |
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Advances in Tracking and Recognition of Human Motion |
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2009 |
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Encyclopedia of Information Science and Technology |
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2nd edition |
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65–71 |
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ADAS @ adas @ ASG2009 |
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1143 |
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