Crowd Density Estimation Using Taylor Expansion and Local Texture Feature
| Autor: | Hsien-Chun Chiu, Chih-Chin Lai |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Estimation
0209 industrial biotechnology business.industry Computer science Pattern recognition 02 engineering and technology Quantitative Biology::Subcellular Processes Support vector machine symbols.namesake 020901 industrial engineering & automation Operator (computer programming) Data_GENERAL 0202 electrical engineering electronic engineering information engineering Taylor series symbols 020201 artificial intelligence & image processing Artificial intelligence Crowd density Texture feature business |
| Zdroj: | ICCE-TW |
| Popis: | Crowd density estimation from images or videos is an important subject for crowd monitoring and safety control. In this paper, we propose a crowd density estimation method based on the Taylor expansion and the local binary count operator. Crowd density classification is performed using a support vector machine. Experiments on the PETS 2009 dataset are provided to demonstrate the feasibility of the proposed approach. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|