| People | Locations | Statistics |
|---|---|---|
| Tekkaya, A. Erman |
| |
| Förster, Peter |
| |
| Mudimu, George T. |
| |
| Shibata, Lillian Marie |
| |
| Talabbeydokhti, Nasser |
| |
| Laffite, Ernesto Dante Rodriguez |
| |
| Schöpke, Benito |
| |
| Gobis, Anna |
| |
| Alfares, Hesham K. |
| |
| Münzel, Thomas |
| |
| Joy, Gemini Velleringatt |
| |
| Oubahman, Laila |
| |
| Filali, Youssef |
| |
| Philippi, Paula |
| |
| George, Alinda |
| |
| Lucia, Caterina De |
| |
| Avril, Ludovic |
| |
| Belachew, Zigyalew Gashaw |
| |
| Kassens-Noor, Eva | Darmstadt |
|
| Cho, Seongchul |
| |
| Tonne, Cathryn |
| |
| Hosseinlou, Farhad |
| |
| Ganvit, Harsh |
| |
| Schmitt, Konrad Erich Kork |
| |
| Grimm, Daniel |
|
With, Phn Peter De
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (14/14 displayed)
- 2018Semiautomatic training and evaluation of a learning-based vehicle make and model recognition system
- 2018Conditional transfer with dense residual attention: synthesizing traffic signs from street-view imagery
- 2017Fast scene analysis for surveillance & video databases
- 2015Combined generation of road marking and road sign databases applied to consistency checking of pedestrian crossings
- 2015Free-space detection using online disparity-supervised color modeling
- 2015A vision-based approach for tramway rail extraction
- 2014Context-based object-of-interest detection for a generic traffic surveillance analysis system
- 2014Extending the stixel world with online self-supervised color modeling for road-versus-obstacle segmentation
- 2014Optimal performance-efficiency trade-off for bag of words classification of road signs
- 2014Mutation detection for inventories of traffic signs from street-level panoramic images
- 2014Exploiting street-level panoramic images for large-scale automated surveying of traffic sign
- 2013Robust classification system with reliability prediction for semi-automatic traffic-sign inventory systems
- 2012Large-scale classification of traffic signs under real-world conditions
- 2011Nighttime vision-based car detection and tracking for smart road lighting system
Places of action
| Organizations | Location | People |
|---|
article
Exploiting street-level panoramic images for large-scale automated surveying of traffic sign
Abstract
Accurate and up-to-date inventories of traffic signs contribute to efficient road maintenance and a high road safety. This paper describes a system for the automated surveying of road signs from street-level images. This is an extremely challenging task, as the involved capturings are non-densely sampled, captured under a wide range of weather conditions and signs may be distorted. The described system is designed in a generic and learning-based fashion, which enables the recognition of different sign appearance classes with the same algorithms, based on class-specific training data. The system starts with detection of the signs visible within each image, using a detection cascade. Next, the 3D position of the signs that are detected consequently within consecutive capturings is calculated. Afterwards, each positioned road sign is classified to retrieve its sign type, thereby exploiting all detections used during positioning of the respective sign. The presented system is intended for large-scale application and currently supports 11 sign appearance classes, containing 176 different sign types. Performance evaluations conducted on a large, real-world dataset (68,010 images) show that our approach accurately positions 95.5 % of the 3,385 present signs, where 96.3 % of them are also correctly classified. Furthermore, our system localized 98.5 % of the signs in at least a single image. Our system design allows for appending a limited manual correction stage to attain a very high performance, so that sign inventories can be created cost effectively.
Topics
Search in FID move catalog