Abstract
The proposal of this study is introducing a new feature, called soft Histogram of Oriented Gradients (SHOG). This feature is designed for traffic sign detection. SHOG differs from traditional (hard) HOG in terms of symmetry information and cell of histogram positions. Unlike hard HOG, SHOG changes the positions of cells to a randomized selection of cells following by symmetry shapes of the traffic sign images. SHOG is implemented on the famous German traffic sign detection benchmark (GTSDB) dataset. Comparing to the conventional HOG feature experimented on GTSDB, SHOG could show better performance while uses smaller feature size.
Original language | English |
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Title of host publication | 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 388-392 |
Number of pages | 5 |
ISBN (Electronic) | 9781509008216 |
DOIs | |
Publication status | Published - 2016 Oct 21 |
Event | 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016 - Xian, China Duration: 2016 Aug 19 → 2016 Aug 22 |
Publication series
Name | 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016 |
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Other
Other | 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016 |
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Country/Territory | China |
City | Xian |
Period | 16/8/19 → 16/8/22 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
All Science Journal Classification (ASJC) codes
- Modelling and Simulation
- Artificial Intelligence
- Control and Optimization