Abstract
Feature extraction is an essential step in various image processing and computer vision tasks, such as object recognition, image retrieval, 3D construction, virtual reality, and so on. Design of feature extraction method is probably the single most important factor in achieving high performance of various tasks. Different applications create different challenges and requirements for the design of visual features. In this paper, we explored and investigated the effectiveness of different combinations of promising local feature detectors and descriptors for non-rigid 3D objects. Different configurations of visual feature detectors and descriptors have been enumerated, and each configuration has been evaluated by image matching accuracy. The results indicated that the scale-invariant feature transform feature detector and descriptor achieved the best overall performance in describing local features of non-rigid 3D object.
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