Pedestrian Detection for UAVs Using Cascade Classifiers with Meanshift
| Autor: | Vanessa Abad, Humberto Parra, Hugo Ruiz, Marco A. Luna, Julio F. Moya, Wilbert G. Aguilar |
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| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
business.industry Computer science Pedestrian detection Detector ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Process (computing) Pattern recognition 02 engineering and technology Pedestrian 020901 industrial engineering & automation Cascade 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence AdaBoost Mean-shift business |
| Zdroj: | ICSC |
| Popis: | In this paper, we propose an algorithm for pedestrian detection focusing on UAV applications. Our proposal is based on a combination of Haar-LBP features with Adaboost for the training process, and Meanshift for improving the performance of the pedestrian detector. We mount a dataset with images captured from surveillance cameras. Our dataset and algorithm are evaluated and compared with other approaches from the literature. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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