Recent Advancements on Drivable Free Space Estimation Using Monocular Vision

This paper presents a overview on recent work on drivable free space estimation with emphasis on monocular vision. Yao et. al. proposed an inference in MRF using various cues based on appearance, edges, spatial and temporal smoothness. Wolcott et. al. added more cues based on perceived motion using...

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Bibliographic Details
Published inBahria University Journal of Information & Communication Technology Vol. 10; no. 1; pp. 51 - 55
Main Authors Amir, Yasir, Rasheed, Haroon, Shahid, Umair
Format Journal Article
LanguageEnglish
Published Karachi Bahria University 01.06.2017
Subjects
Algorithms
Artificial neural networks
Cameras
Dynamic programming
Monocular vision
Neural networks
Optical flow (image analysis)
Roads & highways
Robotics
Smoothness
Vehicles
United Kingdom > UK
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ISSN1999-4974
2304-7593

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Summary:This paper presents a overview on recent work on drivable free space estimation with emphasis on monocular vision. Yao et. al. proposed an inference in MRF using various cues based on appearance, edges, spatial and temporal smoothness. Wolcott et. al. added more cues based on perceived motion using optical flow. While Levi et. al. proposed a new column wise regression approach using convolutional neural networks and stixels. All the techniques reviewed in this paper have large processing time, thus seriously limiting their practical application.
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ISSN:1999-4974
2304-7593