Object setection and recognition in infrared images
In this report, we present a series of object recognition and detection methods on infrared images for surveillance applications. The techniques employed are AdaBoost cascade classification method and support vector machine using histogram of orientation gradients feature descriptors. First, we coll...
Saved in:
| 主要作者: | |
|---|---|
| 其他作者: | |
| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
2015
|
| 主題: | |
| 在線閱讀: | http://hdl.handle.net/10356/63630 |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| 機構: | Nanyang Technological University |
| 語言: | English |
| 總結: | In this report, we present a series of object recognition and detection methods on infrared images for surveillance applications. The techniques employed are AdaBoost cascade classification method and support vector machine using histogram of orientation gradients feature descriptors. First, we collect a set of infrared spectrum images and evaluate the performance of each method. After analyzing a preliminary test using the infrared dataset, we tune the classification criteria and provide suggestions to improve classification and human detection accuracy. Our experiments results show some good overall improvements with better accuracy and lower error rate. |
|---|