Catadioptric vehicle undercarriage imaging with visual path planning

Ross, Robert; Devlin, John; Souza-Daw, Anthony de

doi:10.1109/icara.2011.6144877

Cited by 3 publications

(3 citation statements)

References 10 publications

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“…This technique along with similar implementations [8] assumes a co-planar surface which results in lower areas being slightly stretched and higher areas bunched together in the final mosaic. Several solutions, including dynamic scaling based on height and dynamic adjustment of the search space area are proposed to address this issue, though this implementation doesn't employ either solution [10].…”

Section: B Region Of Interest Generationmentioning

confidence: 99%

“…The final application for this paper is to perform undercarriage imaging of motor vehicles using mobile robots fitted with a catadioptric imaging system as described in [10]. This approach allows for the majority of the accessible areas of the undercarriage to be quickly searched in only two passes from the mobile robot and provides a mosaic image of the undercarriage for operator inspection.…”

Section: Undercarriage Imaging Applicationmentioning

confidence: 99%

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Mobile robot mosaic imaging of vehicle undercarriages using catadioptric vision

Ross

Devlin

Souza-Daw

2012

2012 International Conference on Control, Automation and Information Sciences (ICCAIS)

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This paper describes a technique for performing imaging of car undercarriages using a mobile robot fitted with a catadioptric camera. The mobile robot follows a visual based pre-computed path which trisects the undercarriage whilst the catadioptric camera sensor records a wide angle view of the undercarriage as the robot traverses the undercarriage forwards and backwards. Odometry data from the mobile robot is used to dynamically generate a region of interest, reducing the search space for image registration where the images are stitched together to form a complete undercarriage mosaic, reducing computation time by 18%. In contrast to a regular camera which would require 7 passes, the proposed catadioptric imaging system can image the majority of the undercarriage in 2, reducing image acquisition time by 70%. The technique is verified through mosaicing algorithms applied to experimental data and shows promise for undercarriage explosive detection robots.

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Section: B Region Of Interest Generationmentioning

confidence: 99%

Section: Undercarriage Imaging Applicationmentioning

confidence: 99%

Mobile robot mosaic imaging of vehicle undercarriages using catadioptric vision

Ross

Devlin

Souza-Daw

2012

2012 International Conference on Control, Automation and Information Sciences (ICCAIS)

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“…Finally, catadioptric cameras use a convex mirror rather than a wide-angle lens to capture wide-angle images as illustrated in Figure 1(d). The catadioptric approach not only has a wider field of view compared to dioptric sensors but also has a blind-spot in the centre of the image (where the camera sees a direct reflection of itself in the mirror) (Ross et al, 2011). Also, as a mirror is used, the image captured by the catadioptric sensor will be a mirror image of those taken using a dioptric sensor.…”

Section: Omnidirectional Imaging Techniquesmentioning

confidence: 99%

Design and evaluation of a low-cost street-level image capturing vehicle for south-east Asia

Souza-Daw

Ross

Nhan

et al. 2015

Journal of Engineering, Design and Technology

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Purpose – The purpose of this paper is to present a low-cost, highly mobile system for performing street-level imaging. Street-level imaging and geo-location-based services are rapidly growing in both popularity and coverage. Google Street View and Bing StreetSide are two of the free, online services which allow users to search location-based information on interactive maps. In addition, these services also provide software developers and researchers a rich source of street-level images for different purposes – from identifying traffic routes to augmented reality applications. Currently, coverage for Street View and StreetSide is limited to more affluent Western countries with sparse coverage throughout south-east Asia and Africa. In this paper, we present a low-cost system to perform street-level imaging targeted towards the congested, motorcycle-dominant south-east Asian countries. The proposed system uses a catadioptric imaging system to capture 360-degree panoramic images which are geo-located using an on-board GPS. The system is mounted on the back of a motorcycle to provide maximum mobility and access to narrow roads. An innovative backwards remapping technique for flattening the images is discussed along with some results from the first 150 km which have been captured from Southern Vietnam. Design/methodology/approach – The design was a low-cost prototype design using low-cost off-the-shelf hardware with custom software and assembly to facilitate functionality. Findings – The system was shown to work well as a low-cost omnidirectional mapping solution targeted toward sea-of-motorbike road conditions. Research limitations/implications – Some of the pictures returned by the system were unclear. These could be improved by having artificial lighting (currently only ambient light is used), a gyroscope-stabilised imaging platform and a higher resolution camera. Originality/value – This paper discusses a design which facilitates low-cost, street-level imaging for a sea-of-motorcycle environment. The system uses a catadioptric imaging approach to give a wide field of view without excessive image storage requirements using dozens of cameras.

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Vehicle tyre parameterisation using binary search thresholding and contour fitting

Ross

Devlin

2011

7th International Conference on Broadband Communications and Biomedical Applications

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Catadioptric vehicle undercarriage imaging with visual path planning

Cited by 3 publications

References 10 publications

Mobile robot mosaic imaging of vehicle undercarriages using catadioptric vision

Mobile robot mosaic imaging of vehicle undercarriages using catadioptric vision

Design and evaluation of a low-cost street-level image capturing vehicle for south-east Asia

Vehicle tyre parameterisation using binary search thresholding and contour fitting

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