Abstract
A kind of object recognition algorithm based on Affine Histogram of Oriented Gradient (AHOG+SVM) is proposed to solve the poor effect of object recognition algorithm based on HOG (HOG+SVM). In order to have scale invariance, this paper builds multi-scale pyramid gradient images, and then computes HOG feature on them. In order to increase the rotational invariance and shear invariance, this method firstly expands 2D HOG grid to 3D HOG grid, then maps 3D grid to 2D affine grid according to the relationship between the world coordinate and image coordinate. Finally, inverse transformation of HOG feature in affine grid is carried out to remove the influence of affine transformation. The experimental results show that, the proposed method has the ability to solve the low recognition rate because of scale changes, rotation changes and shear changes (3D perspective changes) of object, and its performance is better than HOG+SVM.
| Original language | English |
|---|---|
| Pages (from-to) | 1428-1434 |
| Number of pages | 7 |
| Journal | Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology |
| Volume | 35 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Jun 2013 |
Keywords
- Affine grid
- Affine transformation
- Histograms of Oriented Gradients (HOG) feature
- Object recognition
- Perspective changes
- Support Vector Machine (SVM)