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Pedestrian recognition using differential Haar-like feature based on Adaboost algorithm to apply intelligence wheelchair
| Content Provider | Semantic Scholar |
|---|---|
| Author | Lee, Sanghun Park, Sang-Hee Lee, Yeung-Hak Seo, Hee-Don |
| Copyright Year | 2010 |
| Abstract | In this paper, we suggest an advanced algorithm, to recognize pedestrian/non-pedestrian using differential haar-like feature, which applies Adaboost algorithm to make a strong classification from weak classifications. First, we extract two feature vectors: horizontal haar-like feature and vertical haar-like feature. For the next, we calculate the proposed feature vector using differential haar-like method. And then, a strong classification needs to be obtained from weak classifications for composite recognition method using the differential area of horizontal and vertical haar-like. In the proposed method, we use one feature vector and one strong classification for the first stage of recognition. Based on our experiment, the proposed algorithm shows higher recognition rate compared to the traditional method for the pedestrian and non-pedestrian. |
| Starting Page | 481 |
| Ending Page | 486 |
| Page Count | 6 |
| File Format | PDF HTM / HTML |
| Volume Number | 31 |
| Alternate Webpage(s) | http://ocean.kisti.re.kr/downfile/volume/kosombe/OOSCB@/2010/v31n6/OOSCB@_2010_v31n6_481.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
