Vision based Vehicle/Pedestrian Detection in Traffic Surveillance System
| Autor: | S. Suryakala, S. Joseph Gladwin, K. Muthumeenakshi |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
021110 strategic
defence & security studies Haar-like features Vision based Computer science Pedestrian detection Vehicle detection Real-time computing 0211 other engineering and technologies 02 engineering and technology Pedestrian Intelligent transportation system Classifier (UML) Object detection |
| Zdroj: | 2019 International Conference on Communication and Signal Processing (ICCSP). |
| Popis: | Vehicle detection and counting plays a major role in Intelligent Transportation Systems, which continuously provides the traffic information. This detection process may face many challenges like different climatic conditions and illumination changes. Detection of Pedestrians is a main concern of car manufacturers to have an automated system which must be able to detect the pedestrian in the surrounding of vehicles. There is a performance degradation with increase in occlusion level. This paper presents the Vehicle and Pedestrian Detection by Haar Cascade Classifier and Background Separation method respectively. Haar Cascade classifier is an efficient method for object detection, first proposed by Viola-Jones. Background Separation method uses K-NN algorithm to identify the pedestrians. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|