Paper
2 February 2012 Tracking white road line by particle filter from the video sequence acquired by the camera attached to a walking human body
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Abstract
This paper proposes a method for tracking and recognizing the white line marked in the surface of the road from the video sequence acquired by the camera attached to a walking human, towards the actualization of an automatic navigation system for the visually handicapped. Our proposed method consists of two main modules: (1) Particle Filter based module for tracking the white line, and (2) CLAFIC Method based module for classifying whether the tracked object is the white line. In (1), each particle is a rectangle, and is described by its centroid's coordinates and its orientation. The likelihood of a particle is computed based on the number of white pixels in the rectangle. In (2), in order to obtain the ranges (to be used for the recognition) for the white line's length and width, Principal Component Analysis is applied to the covariance matrix obtained from valid sample particles. At each frame, PCA is applied to the covariance matrix constructed from particles with high likelihood, and if the obtained length and width are within the abovementioned ranges, it is recognized as the white line. Experimental results using real video sequences show the validity of the proposed method.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shohei Takahashi and Jun Ohya "Tracking white road line by particle filter from the video sequence acquired by the camera attached to a walking human body", Proc. SPIE 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II, 82950V (2 February 2012); https://doi.org/10.1117/12.907814
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Cited by 1 scholarly publication.
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KEYWORDS
Particles

Video

Particle filters

Roads

Visualization

Cameras

Principal component analysis

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