Academic Journal
Efficient Vehicle Detection and Distance Estimation Based on Aggregated Channel Features and Inverse Perspective Mapping from a Single Camera
| العنوان: | Efficient Vehicle Detection and Distance Estimation Based on Aggregated Channel Features and Inverse Perspective Mapping from a Single Camera |
|---|---|
| المؤلفون: | Jong Bae Kim |
| المصدر: | Symmetry, Vol 11, Iss 10, p 1205 (2019) |
| بيانات النشر: | MDPI AG |
| سنة النشر: | 2019 |
| المجموعة: | Directory of Open Access Journals: DOAJ Articles |
| مصطلحات موضوعية: | vehicle detection, vehicle distance estimation, aggregated channel features (acfs), inverse perspective mapping (ipm), advance driver assistance system (adas), Mathematics, QA1-939 |
| الوصف: | In this paper a method for detecting and estimating the distance of a vehicle driving in front using a single black-box camera installed in a vehicle was proposed. In order to apply the proposed method to autonomous vehicles, it was required to reduce the throughput and speed-up the processing. To do this, the proposed method decomposed the input image into multiple-resolution images for real-time processing and then extracted the aggregated channel features (ACFs). The idea was to extract only the most important features from images at different resolutions symmetrically. A method of detecting an object and a method of estimating a vehicle’s distance from a bird’s eye view through inverse perspective mapping (IPM) were applied. In the proposed method, ACFs were used to generate the AdaBoost-based vehicle detector. The ACFs were extracted from the LUV color, edge gradient, and orientation (histograms of oriented gradients) of the input image. Subsequently, by applying IPM and transforming a 2D input image into 3D by generating an image projected in three dimensions, the distance between the detected vehicle and the autonomous vehicle was detected. The proposed method was applied in a real-world road environment and showed accurate results for vehicle detection and distance estimation in real-time processing. Thus, it was showed that our method is applicable to autonomous vehicles. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 2073-8994 |
| Relation: | https://www.mdpi.com/2073-8994/11/10/1205; https://doaj.org/toc/2073-8994; https://doaj.org/article/216344184c814fa9a99761d426eb305f |
| DOI: | 10.3390/sym11101205 |
| الاتاحة: | https://doi.org/10.3390/sym11101205 https://doaj.org/article/216344184c814fa9a99761d426eb305f |
| رقم الانضمام: | edsbas.E8C34A05 |
| قاعدة البيانات: | BASE |
Full Text Finder | تدمد: | 20738994 |
|---|---|
| DOI: | 10.3390/sym11101205 |