Detection and Tracking of Pedestrian in Various Light Condition
DOI:
https://doi.org/10.61841/c0bpx624Keywords:
Pedestrian Detection, Object Detection System, Driver Assistance System, Caltech Pedestrian DatasetAbstract
Surveillance systems are to be effective in the current scenario, for which development is the challenging task for researchers. The major challenge is pedestrian detection in various conditions of light. This can well assist the advanced driver system. In this paper, an approach is considered for pedestrian detection and tracking. It can avoid the collision among vehicles and pedestrians as well. The different conditions of light are considered to be day, night, and fog. Therefore, a dataset is developed also. The results are compared with the standard multispectral dataset KAIST. Experimental results show the performance as high as possible.
Downloads
References
[1] Y. Tian, P. Luo, X. Wang, X. Tang, Pedestrian an detection aided by deep learning semantic tasks, arXiv
preprint, 2014. 〈arXiv:1412.0069〉.
[2] W. Ouyang, X. Wang, A discriminative deep model for pedestrian detection with occlusion handling, in:
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012, pp. 2012,pp.3258–
3265.
[3] National Highway Transportation Safety Administration, TRAFFIC SAFETY FACTS 2012 Data,”
https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812018, 2014, online; accessed 27 July 2016
[4] W. Ouyang, X. Wang, Joint deep learning for pedestrian an detection, in: Proceedings of the IEEE
International Conference on Computer Vision (ICCV), Dec 2013, pp. pp.2056–2063...
[5] D. Olmeda, C. Premebida, U. Nunes, J. Armingol, and A. de la Escalera. Pedestrian classification and
detection in far-infrared images. Integrated Computer-Aided Engineering, 20:347–360, 2013.
[6] P. Ott and M. Everingham, “Implicit color segmentation features for pedestrian and object detection,” in
IEEE Intl. Conf. Computer Vision, 2009.
[7] P. Viola, M. Jones, D. Snow, Detecting pedestrian using patterns of motion and appearance, in:
Proceedings of the 9th IEEE International Conference on Computer Vision, vol. 2, vol.2,Oct2003,pp.734–741.
[8] D. G. Gomez, A global approach to vision-based pedestrian detection for advanced driver assistance
systems. Universitat Aut`onoma de Barcelona, 2010.
[9] D. Gerónimo and A. M. López, Vision-based pedestrian protection systems for intelligent vehicles.
Springer, 2014.
[10] T. Gandhi and M. Trivedi, “Pedestrian protection systems: Issues, survey, and challenges,” IEEE Trans.
Intelligent Transportation Systems, vol. 8, no. 3, pp. 413–430, Sept. 2007.
[11] Y. Zheng, C. Shen, R. Hartley, and X. Huang, “Effective pedestrian detection using center-symmetric local
binary/trinary patterns,” arXiv preprint arXiv:1009.0892, 2010.
[12] W. Nam, P. Dollár, J.H. Han, Local decorrelation for improved pedestrian detection, in: Proceedings of the
28th Annual Conference on Neural Information Processing Systems (NIPS), 2014.
[13] Sermanet, K., Kavukcuoglu, S., Chintala, S., and LeCun, Pedestrian detection with unsupervised multi-stage
feature learning, In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
(CVPR), June 2013, pp. 3626–3633.
[14] Zhang, S., Yang, J., & Schiele, B. (2018). Occluded pedestrian detection through guided attention in CNNs.
In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 6995-7003).
[15] Sodikov, Jamshid. "Road Traffic Accident Data Analysis and Visualization in R." International Journal of
Computer Science Engineering and Information Technology Research (IJCSEITR) 8.3 (2018): 25-32
[16] BAKO, AR, and IJ MUSA. "EFFECT OF LAND USE ON ROAD TRAFFIC ACCIDENTS IN URBAN
ZARIA AREA, NIGERIA." International Journal of Humanities, Arts, Medicine and Sciences (BEST:
IJHAMS) 2.1 (2014):35-42
[17] HUMAYUN MAQBOOL, Dr., SANDEEP SINGLA, and ANUJ SACHAR. "DESIGN AND
DEVELOPMENT OF INTELLIGENT TRANSPORTATION SYSTEM IN LAL CHOWK, SRINAGAR,
JAMMU AND KASHMIR." International Journal of Civil, Structural, Environmental and Infrastructure
Engineering Research and Development (IJCSEIERD) 10.2 (2020): 9–16
[18] HINGMIRE, VISHAL S., and SUNITA S. SHINDE. "IMPLEMENTATION OF AN INTEGRATED
SYSTEM FOR ACCURATE LOCALIZATION." International Journal of Computer Networking, Wireless
and Mobile Communications (IJCNWMC) 3.3 (2013): 117-124
[19] Sherasiya, Tariqahmad, Hardik Upadhyay, and Hiren B. Patel. "A survey: Intrusion detection system for
internet of things." International Journal of Computer Science and Engineering (IJCSE) 5.2 (2016): 91-98.
[20] MATHUR, GEETIKA, HARSHIT SHARMA, and RISHABH PANDEY. "A STUDY ON SELF-DRIVING CARS: AN APPLICATION OF IoT." International Journal of Computer Networking, Wireless and Mobile Communications (IJCNWMC) 9.1 (2019): 25-34
[21] MALVADKAR, PUJA, and RAMESHWAR KAWITKAR. "REAL-TIME SYSTEM FOR DETECTING DISTRACTION OF DRIVER." International Journal of Electronics and Communication Engineering (IJECE) 2.3 (2013): 85-90
[22] GUPTA, PRIYA, NIVEDITA KUMARI, and SHIKHA GUPTA. "VIDEO SEGMENTATION FOR MOVING OBJECT DETECTION & TRACKING-A REVIEW." International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR) 5.4 (2015):17-): 17-34
Downloads
Published
Issue
Section
License
Copyright (c) 2020 AUTHOR
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
