期刊論文
| 學年 | 104 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2016-04-01 |
| 作品名稱 | Graphics processing unit-accelerated multi-resolution exhaustive search algorithm for real-time keypoint descriptor matching in high-dimensional spaces |
| 作品名稱（其他語言） | |
| 著者 | Chi-Yi Tsai; Chih-Hung Huang; An-Hung Tsao |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | IET Computer Vision 10(3), pp.212-219 |
| 摘要 | Image keypoint descriptor matching is an important pre-processing task in various computer vision applications. This study first introduces an existing multi-resolution exhaustive search (MRES) algorithm combined with a multi-resolution candidate elimination technique to address this issue efficiently. A graphics processing unit (GPU) acceleration design is then proposed to improve its real-time performance. Suppose that a scale-invariant feature transform like algorithm is used to extract image keypoint descriptors of an input image, the MRES algorithm first computes a multi-resolution table of each keypoint descriptor by using a L1-norm-based dimension reduction approach. Next, a fast candidate elimination algorithm is employed based on the multi-resolution tables to remove all non-candidates from a candidate matching list by using a simple L1-norm computation. However, when the MRES algorithm was implemented on the central processing unit, the authors observed that the step of multi-resolution table building is not computationally efficient, but it is very suitable for parallel implementation on the GPU. Therefore, this study presents a GPU acceleration method for the MRES algorithm to achieve better real-time performance. Experimental results validate the computational efficiency and matching accuracy of the proposed algorithm by comparing with three existing methods. |
| 關鍵字 | |
| 語言 | en |
| ISSN | 1751-9632 1751-9640 |
| 期刊性質 | 國外 |
| 收錄於 | SCI EI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | GBR |
| 公開徵稿 | |
| 出版型式 | ,電子版,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/106170 ) |