Abstract
Researchers gave the vehicle and pedestrian detection lots of attention to alarm the drivers for improving the safety of transportation systems. However, bicycles are also the significant factor of the safety on road. In this paper, a bicycle detector for side-view image is proposed based on the observation that a bicycle consists of two wheels in the form of ellipse shapes and a frame in the form of two triangles. Through the design of geometric constrains between the triangles and ellipses, the computation is fast comparing to the feature-based classifiers. Besides, the training process is unnecessary and only single image is required for our algorithm. Preliminary experimental result is also given in this paper to show the practicability and the performance of the proposed bicycle model and bicycle detection algorithm.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2016 SAI Computing Conference, SAI 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 349-353 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781467384605 |
| DOIs | |
| Publication status | Published - 2016 Aug 29 |
| Event | 2016 SAI Computing Conference, SAI 2016 - London, United Kingdom Duration: 2016 Jul 13 → 2016 Jul 15 |
Other
| Other | 2016 SAI Computing Conference, SAI 2016 |
|---|---|
| Country | United Kingdom |
| City | London |
| Period | 16-07-13 → 16-07-15 |
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All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Information Systems
- Signal Processing
- Modelling and Simulation
Cite this
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A fast bicycle detector based on a geometric model for single side-view image. / Young, Chung-Ping; Lin, Yen Bor; Chen, Kuan Yu.
Proceedings of 2016 SAI Computing Conference, SAI 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 349-353 7556005.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - A fast bicycle detector based on a geometric model for single side-view image
AU - Young, Chung-Ping
AU - Lin, Yen Bor
AU - Chen, Kuan Yu
PY - 2016/8/29
Y1 - 2016/8/29
N2 - Researchers gave the vehicle and pedestrian detection lots of attention to alarm the drivers for improving the safety of transportation systems. However, bicycles are also the significant factor of the safety on road. In this paper, a bicycle detector for side-view image is proposed based on the observation that a bicycle consists of two wheels in the form of ellipse shapes and a frame in the form of two triangles. Through the design of geometric constrains between the triangles and ellipses, the computation is fast comparing to the feature-based classifiers. Besides, the training process is unnecessary and only single image is required for our algorithm. Preliminary experimental result is also given in this paper to show the practicability and the performance of the proposed bicycle model and bicycle detection algorithm.
AB - Researchers gave the vehicle and pedestrian detection lots of attention to alarm the drivers for improving the safety of transportation systems. However, bicycles are also the significant factor of the safety on road. In this paper, a bicycle detector for side-view image is proposed based on the observation that a bicycle consists of two wheels in the form of ellipse shapes and a frame in the form of two triangles. Through the design of geometric constrains between the triangles and ellipses, the computation is fast comparing to the feature-based classifiers. Besides, the training process is unnecessary and only single image is required for our algorithm. Preliminary experimental result is also given in this paper to show the practicability and the performance of the proposed bicycle model and bicycle detection algorithm.
UR - http://www.scopus.com/inward/record.url?scp=84988841549&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84988841549&partnerID=8YFLogxK
U2 - 10.1109/SAI.2016.7556005
DO - 10.1109/SAI.2016.7556005
M3 - Conference contribution
SP - 349
EP - 353
BT - Proceedings of 2016 SAI Computing Conference, SAI 2016
PB - Institute of Electrical and Electronics Engineers Inc.
ER -