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Author  |
Zhijie Fang; David Vazquez; Antonio Lopez |
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Title |
On-Board Detection of Pedestrian Intentions |
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Journal Article |
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2017 |
Publication |
Sensors |
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SENS |
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17 |
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10 |
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2193 |
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Keywords |
pedestrian intention; ADAS; self-driving |
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Abstract |
Avoiding vehicle-to-pedestrian crashes is a critical requirement for nowadays advanced driver assistant systems (ADAS) and future self-driving vehicles. Accordingly, detecting pedestrians from raw sensor data has a history of more than 15 years of research, with vision playing a central role.
During the last years, deep learning has boosted the accuracy of image-based pedestrian detectors.
However, detection is just the first step towards answering the core question, namely is the vehicle going to crash with a pedestrian provided preventive actions are not taken? Therefore, knowing as soon as possible if a detected pedestrian has the intention of crossing the road ahead of the vehicle is
essential for performing safe and comfortable maneuvers that prevent a crash. However, compared to pedestrian detection, there is relatively little literature on detecting pedestrian intentions. This paper aims to contribute along this line by presenting a new vision-based approach which analyzes the
pose of a pedestrian along several frames to determine if he or she is going to enter the road or not. We present experiments showing 750 ms of anticipation for pedestrians crossing the road, which at a typical urban driving speed of 50 km/h can provide 15 additional meters (compared to a pure pedestrian detector) for vehicle automatic reactions or to warn the driver. Moreover, in contrast with state-of-the-art methods, our approach is monocular, neither requiring stereo nor optical flow information. |
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ADAS; 600.085; 600.076; 601.223; 600.116; 600.118 |
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Admin @ si @ FVL2017 |
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2983 |
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Author |
Zhong Jin; Franck Davoine |
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Title |
Orthogonal ICA Representation Of Images |
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Miscellaneous |
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2004 |
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8th International Conference on Control, Automation, Robotics and Vision, 369–374 |
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Kunming (China) |
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Admin @ si @ JiD2004 |
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499 |
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Author |
Zhong Jin; Franck Davoine; Zhen Lou |
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Title |
Facial expression analysis by using KPCA |
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Miscellaneous |
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2003 |
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IEEE International Conference on Robotics, Intelligent Systems and Signal Processing (IEEE RISSP 2003), pp736–741 |
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Changsha, Hunan, China |
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Admin @ si @ JDL2003 |
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431 |
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Zhong Jin; Franck Davoine; Zhen Lou |
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Title |
An Effective EM Algorithm for PCA Mixture Model |
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2004 |
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Structural and Statistical Pattern Recognition, Lecture Notes in Computer Science, 3138:626–634 |
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Lisbon, Portugal |
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Admin @ si @ JDL2004 |
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482 |
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Author |
Zhong Jin; Franck Davoine; Zhen Lou; Jing-Yu Yang |
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Title |
A novel PCA-based Bayes classifier and face analysis |
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2006 |
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International Conference on Advances in Biometrics (ICB’06), LNCS 3832: 144–150 |
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Hong Kong |
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Admin @ si @ JDL2006 |
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624 |
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Author |
Zhong Jin; Jing-Yu Yang; Zhen Lou |
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Title |
A luminance-conditional distribution model of skin color information |
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Miscellaneous |
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2005 |
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2005 Beijing International Conference on Imaging: Technology and Applications for the 21th Century, 280–281 |
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Beijing (China) |
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Admin @ si @ JYL2005 |
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628 |
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Author |
Zhong Jin; Zhen Lou; Jing-Yu Yang; Quan-sen Sun |
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Title |
Face detection using template matching and skin color information |
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Miscellaneous |
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2005 |
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International Conference on Intelligent Computing, 636–645 |
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Hefei (China) |
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Admin @ si @ JLY2005 |
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627 |
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Author |
Zhong Jin; Zhen Lou; Jing-Yu Yang; Quan-sen Sun |
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Title |
Face Detection using Template Matching and Skin-color Information |
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2007 |
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Neurocomputing, 70(4–6): 794–800 |
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Admin @ si @ JLY2007 |
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878 |
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