Digital Image Processing: PIKS Inside
Digital Image Processing: PIKS Inside
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Fusing Points and Lines for High Performance Tracking
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Machine learning for high-speed corner detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
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The paper presents a comparison of key point selection methods used for recognition of objects in scenes recorded by a built-in mobile phone camera. The detected key points include corners and line crossings. An application for Android smartphones was developed utilizing the Features from Accelerated Segment Test (FAST) and Scale-Invariant Feature Transform (SIFT), which was specially modified for processing low resolution images. The implemented algorithm computes descriptors which are invariant to image acquisition settings such as: rotation, noise, scale and brightness variations. The proposed image classification algorithm is based on pairing key points based on similarity of their descriptors.