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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yameng Wang Huicheng Lian Pei Chen Zhenzhen Lu |
| Copyright Year | 2014 |
| Description | Author affiliation: Sch. of Comput. Eng. & Sci., Shanghai Univ., Shanghai, China (Yameng Wang; Huicheng Lian; Pei Chen; Zhenzhen Lu) |
| Abstract | A special and simple method is proposed to improve people counting by adopting low-leveled feature extraction and pattern predicting techniques. Firstly, we use a morphological background modeling and a Gaussian masking method to distinguish moving targets more effectively from video frames. Then, we proposed a Histogram of Oriented Gradient (HOG) feature extraction to catch more meaningful characteristics of appearance and shape of pedestrians. Other features such as edge features and texture features, are integrated as inputs to learn a support vector regression machine and finally to predict the number of pedestrians on a video frame. The experimental results indicate that our proposed method has better performance than other methods, on both database of [4] and ours. |
| Starting Page | 139 |
| Ending Page | 143 |
| File Size | 483863 |
| Page Count | 5 |
| File Format | |
| ISSN | 21579563 |
| e-ISBN | 9781479951512 |
| DOI | 10.1109/ICNC.2014.6975824 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-08-19 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Support vector machines Image segmentation Histograms Accuracy Image edge detection Feature extraction Kernel |
| Content Type | Text |
| Resource Type | Article |
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