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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Siagian, C. Itti, L. |
| Copyright Year | 2004 |
| Abstract | We present a robot localization system using biologically inspired vision. Our system models two extensively studied human visual capabilities: (1) extracting the ldquogistrdquo of a scene to produce a coarse localization hypothesis and (2) refining it by locating salient landmark points in the scene. Gist is computed here as a holistic statistical signature of the image, thereby yielding abstract scene classification and layout. Saliency is computed as a measure of interest at every image location, which efficiently directs the time-consuming landmark-identification process toward the most likely candidate locations in the image. The gist features and salient regions are then further processed using a Monte Carlo localization algorithm to allow the robot to generate its position. We test the system in three different outdoor environments-building complex (38.4 m times 54.86 m area, 13 966 testing images), vegetation-filled park (82.3 m times 109.73 m area, 26 397 testing images), and open-field park (137.16 m times 178.31 m area, 34 711 testing images)-each with its own challenges. The system is able to localize, on average, within 0.98, 2.63, and 3.46 m, respectively, even with multiple kidnapped-robot instances. |
| Sponsorship | IEEE Robotics and Automation Society |
| Starting Page | 861 |
| Ending Page | 873 |
| Page Count | 13 |
| File Size | 1486023 |
| File Format | |
| ISSN | 15523098 |
| Volume Number | 25 |
| Issue Number | 4 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-08-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Mobile robots Layout System testing Humans Intelligent sensors Global Positioning System Robot localization Neuroscience Image recognition Robustness scene recognition Computational neuroscience gist of a scene image classification image statistics landmark recognition robot localization robot vision saliency |
| Content Type | Text |
| Resource Type | Article |
| Subject | Control and Systems Engineering Electrical and Electronic Engineering Computer Science Applications |
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