Determining Noise Performance of Co-Occurrence GMuLBP on Object Detection Task
Küçük Resim Yok
Tarih
2013
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Spie-Int Soc Optical Engineering
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Object detection is currently one of the most actively researched areas of computer vision, image processing and analysis. Image co-occurrence has shown significant performance on object detection task because it considers the characteristic of objects and spatial relationship between them simultaneously. CoHOG has achieved great success on different object detection tasks, especially human detection. Whereas, CoHOG is sensitive to noise and it does not consider gradient magnitude which significantly effects the object detection accuracy. To overcome these disadvantages the CoGMuLBP was proposed. CoGMuLBP uses a new statistical orientation assignment method based on uniform LBP instead of using the common gradient orientation In this study, detection accuracies of CoGMuLBP and CoHOG are calculated on three different datasets with NN classifier. In addition, to evaluate the noise performance of the methods, gaussian noises were added to test images and performances were recalculated. Numerical experiments performed on three different datasets show that 1) CoGMuLBP has higher detection accuracy than CoHOG; 2) using uniform LBP based gradient orientation improves detection accuracy; and 3) CoGMuLBP is more robust to gaussian noise and illumination changes. These results provide the effectiveness of CoGMuLBP for object detection.
Açıklama
6th International Conference on Machine Vision (ICMV) -- NOV 16-17, 2013 -- London, ENGLAND
Anahtar Kelimeler
Object Detection, CoHOG, CoGMuLBP
Kaynak
Sixth International Conference on Machine Vision (Icmv 2013)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
9067
