Object Proposal Generator for Vehicle Detection in Nighttime
| Autor: | O. V. Ramana Murthy, Jyoti Dubey |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
050210 logistics & transportation
Computer science business.industry 05 social sciences Feature extraction 02 engineering and technology Object (computer science) Object detection Statistical classification Feature (computer vision) Sliding window protocol 0502 economics and business 0202 electrical engineering electronic engineering information engineering Benchmark (computing) 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Intelligent transportation system |
| Zdroj: | 2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC). |
| DOI: | 10.1109/iccic.2017.8524263 |
| Popis: | Object Proposal methods are pre-processing steps for detecting objects and vehicles in motion in intelligent transportation systems. Most of the object detection algorithms in literature are developed on daytime datasets and do not produce satisfactory results for nighttime images. This paper presents an approach to generate object proposal for detecting vehicles at night time. Different feature weights, proposals, sliding window are combined to generate a set of proposals to locate probable regions for vehicle detection at night-time. Sun Yat-sen University benchmark dataset is used for validation. This dataset contains images of night time vehicles in two different conditions. One being the vehicles on urban road with lamps and the other on urban road without lamps. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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