Feature-based ROI generation for stereo-based pedestrian detection
| Autor: | Joohee Kim, Maral Mesmakhosroshahi, Maziar Loghman |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Computer science
business.industry Pedestrian detection Feature vector Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Support vector machine ComputingMethodologies_PATTERNRECOGNITION Histogram of oriented gradients Feature (computer vision) Region of interest Computer vision Artificial intelligence business Stereo camera |
| Zdroj: | ICASSP |
| DOI: | 10.1109/icassp.2017.7952452 |
| Popis: | Region of interest (ROI) generation is an important step in stereo-based pedestrian detection systems. In this paper, we propose an ROI generation method by fusing the color and depth information obtained from a stereo camera mounted on a vehicle. In our proposed method, a feature-based method which uses contour properties of the image is used to find the ROIs. In our feature-based ROI extraction method, we extract four features which are contour density, maximum area, maximum perimeter and matching score. Then we create a feature vector from these features and classify them using SVM. ROIs are then classified into the pedestrian and non-pedestrian classes using Histogram of Oriented Gradients (HOG)/Linear SVM. We have tested our proposed method on the Daimler dataset and experimental results show that our proposed method has a 96.5% accuracy for 1 false positive per frame and outperforms existing monocular and stereo-based methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|