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| Content Provider | IET Digital Library |
|---|---|
| Author | Ryu, Hyejeong Chung, Wan Kyun |
| Abstract | A combined method involving global and local descriptors was developed to recognise scenes for loop closure detection in low-textured environments. An omnidirectional image is divided into background regions and salient regions according to the colour distribution. To represent a scene with features that are appropriate to its characteristics, global features for background regions are calculated and scale invariant feature transform features for salient regions are extracted. The proposed method can compute a more distinct scene similarity, and this was verified by an experiment involving loop closure detection. |
| Starting Page | 368 |
| Ending Page | 370 |
| Page Count | 3 |
| ISSN | 00135194 |
| Volume Number | 50 |
| e-ISSN | 1350911X |
| Issue Number | Issue 5, Feb (2014) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/el/50/5 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/el.2013.3505 |
| Journal | Electronics Letters |
| Publisher Date | 2014-02-21 |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Background Regions Colour Distribution Computer Vision And Image Processing Technique Feature Extraction Global Descriptors Image Colour Analysis Image Recognition Image Representation Image Texture Integral Transforms Local Descriptors Loop Closure Detection Low-textured Environments Mobile Robot Navigation Mobile Robots Object Detection Object Recognition Omnidirectional Image Path Planning Robot Vision Salient Region Scale Invariant Feature Transform Feature Extraction Scene Recognition Scene Representation SIFT Transform |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering |
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