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Data for Cooperative object classification for driving applications
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Arnold, Eduardo, Al-Jarrah, Omar Y., Dianati, Mehrdad, Fallah, Saber, Oxtoby, David and Mouzakitis, Alexandros (2021) Data for Cooperative object classification for driving applications. [Dataset]
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Plain Text (Readme file)
README.txt - Published Version Available under License Creative Commons Attribution 4.0. Download (580b) |
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Archive (ZIP) (Dataset)
coopclassificationdataset.zip - Published Version Available under License Creative Commons Attribution 4.0. Download (165Mb) |
Official URL: http://wrap.warwick.ac.uk/160228/
Abstract
3D object classification can be realised by rendering views of the same object from different angles and aggregating all the views to build a classifier. Although this approach has been previously proposed for general objects classification, most existing works did not consider visual impairments. In contrast, this paper considers the problem of 3D object classification for driving applications under impairments (e.g. occlusion and sensor noise) by generating an application-specific dataset. We present a cooperative object classification method where multiple images of the same object seen from different perspectives (agents) are exploited to generate more accurate classification. We consider model generalisation capability and its resilience to impairments. We introduce an occlusion model with higher resemblance to real-world occlusion and use a simplified sensor noise model. The experimental results show that the cooperative model, relying on multiple views, significantly outperforms single-view methods and is effective in mitigating the effects of occlusion and sensor noise.
| Item Type: | Dataset | |||||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software R Medicine > RE Ophthalmology T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) |
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | |||||||||
| Type of Data: | Compressed image files | |||||||||
| Library of Congress Subject Headings (LCSH): | Three-dimensional modeling, Pattern recognition systems, Shapes -- Computer simulation, Vision disorders, Computer vision | |||||||||
| Publisher: | Warwick Manufacturing Group | |||||||||
| Official Date: | 18 November 2021 | |||||||||
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| Status: | Not Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Open Access (Creative Commons) | |||||||||
| Copyright Holders: | University of Warwick | |||||||||
| Description: | This dataset was used in the paper "Cooperative Object Classification for Driving Applications" published in the 2019 IEEE Intelligent Vehicles Symposium (IV). The dataset contains images of a diverse set of objects rendered from three distinct view-points and was created to illustrate the benefits of cooperative (multi-view) object classification amid occlusions and sensor noise. The open access version of this paper is available at The source code is available at |
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| Date of first compliant deposit: | 18 November 2021 | |||||||||
| Date of first compliant Open Access: | 18 November 2021 | |||||||||
| RIOXX Funder/Project Grant: |
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