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Design of a Simulation System for Cross-Eye Dynamic Jamming Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Vehicle Tracking Based on Structured Output SVM Using Retinex and Mutual Information

Authors : Longqi Wang, Xinyang Li, Guanyu Lin, Wei Pei, Guanrong Wang

Published in: Proceedings of 2017 Chinese Intelligent Automation Conference

Publisher: Springer Singapore

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Abstract

At present, most vehicle tracking algorithms are tested in an ideal environment (definition video, without attitude change, without occlusion). However, due to the vehicle variability (scale change, attitude change) and complexity (noise, occlusion) of the surrounding environment in real-life scenarios, there are still many difficulties for the vehicle target accurately tracking. In order to adapt to blur, occlusion, fast moving, illumination change and other complex situation in real scene, the multi-scale Retinex image enhancement algorithm and the mutual information occlusion processing algorithm are introduced into structured output SVM tracking algorithm. Experiments show that the tracking accuracy and robustness of the method are improved significantly on the premise of tracking task performance in the above case.

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previous chapter Research of Localization Method Based on Virtual Reference Points in Robot Auditory System
next chapter Neural Network-Based Self-triggered Attitude Control of a Rigid Spacecraft
Literature
1.
De WC, Proctor AA, Johnson EN (2003) Vision-only aircraft flight control. The 22nd digital avionics systems conference vol 2, pp 8.B.2-81–11
2.
Davidson C, Blake A (1998) Error-tolerant visual planning of planar grasp. Sixth international conference on computer vision, pp 911–916
3.
Ayache N, Cohen I, Herlin I (1992) Medical image tracking. Active Vision MIT Press
4.
Angella F, Reithler L, Gallesio F (2007) Optimal deployment of cameras for video surveillance systems. In: IEEE Conference on Advanced Video and Signal Based Surveillance, pp 388–392
5.
Wang X, Fang L, Chong Z-H (2010) Research on video vehicle tracking algorithm based on Kalman and particle filter.J Image Graph 15(11):615–1622
6.
Wei LK, Wei YK, Yit KC, Mei YC, Teo KTK (2012) Enhancement of particle filter resampling in vehicle tracking via genetic algorithm. In: Sixth UKSim/AMSS European Symposium on Computer Modeling and Simulation (EMS), pp 243–248, 14–16 Nov 2012
7.
Singer RA (1970) Estimating optimal tracking filter performance for manned Maneu-vering Targets. IEEE Trans Aerosp Electron Syst AES 6(4):473–483CrossRef
8.
Candamo J, Shreve MA, Goldgof DB, Sapper DB (2010) Understanding transit scenes: a survey on human behavior-recognition algorithms. IEEE Trans Intell Transp Syst 11(1):206–224CrossRef
9.
Malladi R, Sethian JA (1996) Level set and fast marching methods in image processing and computer vision. Int Conf Image Processing 1:489–492
10.
Michael K, Andrew W, Demetri T (1988) Snakes: active contour models. Int J Comput Vision 1(4):321–331CrossRef
11.
Zhang H, Dong Y, Xia Y (2007) Vehicle tracking algorithm based on modified GVF-snake model. PR AI 20(3):388–393
12.
Roya R, Mansour J (2005) Real time classification and tracking of multiple vehicles in highways. Pattern Recogn Lett 26(10):1597–1607CrossRef
13.
Tao G, Zheng-guang L, Junetc Z (2010) Traffic vehicle contour tracking and its engineering application. J Basic Sci Eng 18(2):343–351
14.
Horn BKP, Schunck BG (1981) Determining optical flow. Artif Intell 17(1–3):185–203CrossRef
15.
Comaniciu D, Ramesh V, Meer P (2000) Real time tracking of non-rigid objects using mean shift. Comput Vision Pattern Recogn 2:142–149
16.
Avidan S (2004) Support vector tracking. Pattern Anal Mach Intelligence IEEE Trans 26(8):1064–1072CrossRef
17.
Li X, Yao X, Murphey YL et al (2004) A real-time vehicle detection and tracking system in outdoor traffic scenes. In: IEEE Conference on Pattern Recognition, Cambridge, pp 761–764
18.
Xie Y, Zhang W (2014) Discriminative object tracking via sparse representation and online dictionary learning. Cybern IEEE Trans 44(4):539–553CrossRef
19.
Hare S, Saffari A, Torr PHS (2011) Struck: structured output tracking with kernels. International conference on computer vision (ICCV), 2011. In: IEEE international conference pp 263–270
20.
Jobson DJ, Rahman Z, Woodell GA (1997) A multi-scale Retinex for bridging the gap between color images and the human observation of scenes. IEEE Trans Image Processing 6(7):965–976CrossRef
21.
Land E (1964) The Retinex. Amer Scient 52(2):247–264
22.
Bin R (2009) Research and implementation of image enhancement algorithm based on Retinex. Master’s degree thesis of Nanjing University of Science and Technology 5:6–7
23.
Jobson DJ, Rahman Z-U, Woodell GA (1997) Properties and performance of a center/surround Retinex. IEEE Trans Image Processing 6(3):451–462CrossRef
24.
Wang M, Zhou S (2011) The study of color image defogging based on wavelet transform and single scale Retinex. Advances in imaging detectors and applications. In: Proceedings of SPIE, vol 8194, pp 1–5
25.
Barnard K, Funt B (1999) Investigations into multi-scale Retinex in colour imaging. Vision and Technology, New York, pp 9–17
Metadata
Title
Vehicle Tracking Based on Structured Output SVM Using Retinex and Mutual Information
Authors
Longqi Wang
Xinyang Li
Guanyu Lin
Wei Pei
Guanrong Wang
Copyright Year
2018
Publisher
Springer Singapore
Book
Proceedings of 2017 Chinese Intelligent Automation Conference

Print ISBN: 978-981-10-6444-9

Electronic ISBN: 978-981-10-6445-6

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-6445-6_76