원문정보
보안공학연구지원센터(IJMUE)
International Journal of Multimedia and Ubiquitous Engineering
Vol.8 No4
2013.07
pp.329-342
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
This paper proposes a robust real-time artificial landmarks detection and recognition system for indoor mobile robot. Landmarks detection and recognition for indoor robots faces two major difficulties, one is the illumination changes and the other is processing speed. In this paper, first, histograms of oriented gradient (HOG) features are extracted to resolve the problem of illumination changes. Second, AdaBoost based algorithm is used in detection phase to increase the processing speed. Finally, RBF-SVM classifier is used for recognition. Experimental results show a high detection and recognition accuracy and the processing speed is about 10 frames per second.
목차
Abstract
1. Introduction
2. Feature extraction
3. Landmark Detection based on AdaBoost
3.1. Using Integral Image to Calculate the HOG Feature for High Speed
3.2. Constructing Weak Classifier of HOG Adapt to AdaBoost
3.3. Strong Classifier
4. The Landmark Recognition based on RBFSVM
4.1. Establishment of SVM Classifier
5. Experimental Results and Analysis
5.1. Experimental Results of Landmark Detection
5.2. Experimental Results based on SVM Landmark Recognition
5.3. The Performance of our Overall System
6. Conclusions
Acknowledgements
References
1. Introduction
2. Feature extraction
3. Landmark Detection based on AdaBoost
3.1. Using Integral Image to Calculate the HOG Feature for High Speed
3.2. Constructing Weak Classifier of HOG Adapt to AdaBoost
3.3. Strong Classifier
4. The Landmark Recognition based on RBFSVM
4.1. Establishment of SVM Classifier
5. Experimental Results and Analysis
5.1. Experimental Results of Landmark Detection
5.2. Experimental Results based on SVM Landmark Recognition
5.3. The Performance of our Overall System
6. Conclusions
Acknowledgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보