A Vision-Based On-road Vehicle Light Detection System Using Support Vector Machines
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Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-10-8797-4_13
Reference14 articles.
1. Arunnehru, J., and M. Kalaiselvi Geetha. 2013. Motion intensity code for action recognition in video using PCA and SVM. In Mining Intelligence and Knowledge Exploration, 70–81. Cham: Springer.
2. Lu, Jianbo, Hassen Hammoud, Todd Clark, Otto Hofmann, Mohsen Lakehal-ayat, Shweta Farmer, Jason Shomsky, and Roland Schaefer. 2017. A System for Autonomous Braking of a Vehicle Following Collision. No. 2017–01–1581. SAE Technical Paper.
3. Zhang, Bailing, Yifan Zhou, Hao Pan, and Tammam Tillo. 2014. Hybrid model of clustering and kernel autoassociator for reliable vehicle type classification. Machine Vision and Applications 25 (2): 437–450.
4. Almagambetov, Akhan, Senem Velipasalar, and Mauricio Casares. 2015. Robust and computationally lightweight autonomous tracking of vehicle taillights and signal detection by embedded smart cameras. IEEE Transactions on Industrial Electronics 62 (6): 3732–3741.
5. Hillel, Aharon Bar, Ronen Lerner, Dan Levi, and Guy Raz. 2014. Recent progress in road and lane detection: a survey. Machine Vision And Applications 25 (3): 727–745.
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