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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Comparison of Key Point Detectors in SIFT Implementation for Mobile Devices
verfasst von : Karol Matusiak, Piotr Skulimowski
Erschienen in: Computer Vision and Graphics
Verlag: Springer Berlin Heidelberg
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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.