Moving object detection under dynamic background in 3D range data

IEEE Intelligent Vehicles Symposium, Proceedings

Volumn , Issue , 2014, Pages 394-399

  Yi, Yang ^a   Guang, Yan ^a   Hao, Zhu ^a   Meng Yin, Fu ^a   Mei Ling, Wang ^a  

^a BEIJING INSTITUTE OF TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; MOTION COMPENSATION;

CHARACTERISTICS OF DYNAMICS; DYNAMIC BACKGROUND; GAUSSIAN MIXTURE MODEL; MOVING OBJECT DETECTION ALGORITHMS; MOVING-OBJECT DETECTION; PROFILE FEATURES; RESEARCH TOPICS; UNSUPERVISED ALGORITHMS;

OBJECT RECOGNITION;

EID: 84905365970     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IVS.2014.6856426     Document Type: Conference Paper

References (16)

1. Yi, Yang, et al. "Lane recognition self-learning scheme of mobile robot based on integrated perception system." Intelligent Vehicles Symposium (IV), 2013 IEEE. IEEE, 2013.
2. Yi, Yang, et al. "Autonomous ground vehicle navigation method in complex environment." Intelligent Vehicles Symposium (IV), 2010 IEEE. IEEE, 2010.
3. Vamborg, F. S. E., V. Brovkin, and M. Claussen. "The effect of a dynamic background albedo scheme on Sahel/Sahara precipitation during the mid-Holocene." Climate of the Past 7.1 (2011): 117-131.
4. Cucchiara, Rita, et al. "Detecting moving objects, ghosts, and shadows in video streams." Pattern Analysis and Machine Intelligence, IEEE Transactions on 25.10 (2003): 1337-1342.
5. Behrad, Alireza, et al. "A robust vision-based moving target detection and tracking system." the Proceeding of Image and Vision Computing Conference. 2001.
6. Elhabian, Shireen Y., Khaled M. El-Sayed, and Sumaya H. Ahmed. "Moving object detection in spatial domain using background removal techniques-state-of-art." Recent patents on computer science 1.1 (2008): 32-54.
7. Ilas, Constantin. "Electronic sensing technologies for autonomous ground vehicles: A review." Advanced Topics in Electrical Engineering (ATEE), 2013 8th International Symposium on. IEEE, 2013.
8. Teichman, Alex, Jesse Levinson, and Sebastian Thrun. "Towards 3d object recognition via classification of arbitrary object tracks." Robotics and Automation (ICRA), 2011 IEEE International Conference on. IEEE, 2011.
9. Held, David, Jesse Levinson, and Sebastian Thrun. "A probabilistic framework for car detection in images using context and scale." Robotics and Automation (ICRA), 2012 IEEE International Conference on. IEEE, 2012.
10. L. Spinello, R. Triebel, and R. Siegwart, "Multimodal people detection and tracking in crowded scenes," in Proc. of The AAAI Conference on Artificial Intelligence (Physically Grounded AI Track), 2008.
11. Azim, Asma, and Olivier Aycard. "Detection, classification and tracking of moving objects in a 3D environment." Intelligent Vehicles Symposium (IV), 2012 IEEE. IEEE, 2012.
12. Kaestner, Ralf, et al. "Generative object detection and tracking in 3d range data." Robotics and Automation (ICRA), 2012 IEEE International Conference on. IEEE, 2012.
13. Hornung, Armin, et al. "OctoMap: an efficient probabilistic 3D mapping framework based on octrees." Autonomous Robots (2013): 1-18.
14. Zhao, Yipu, et al. "Computing object-based saliency in urban scenes using laser sensing." Robotics and Automation (ICRA), 2012 IEEE International Conference on. IEEE, 2012.
15. Kästner, Ralf, et al. "A Bayesian approach to learning 3d representations of dynamic environments." Proc. of The 12th International Symposium on Experimental Robotics (ISER). 2010.
16. Bailey, Timothy L., and Charles Elkan. "Fitting a mixture model by expectation maximization to discover motifs in biopolymers." (1994): 28-36.