The affine scale-invariant feature transform (asift) algorithm is a feature extraction algorithm with affinity and scale invariance, which is suitable for image feature matching using unmanned aerial vehicles (UAVs). ...
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The affine scale-invariant feature transform (asift) algorithm is a feature extraction algorithm with affinity and scale invariance, which is suitable for image feature matching using unmanned aerial vehicles (UAVs). However, there are many problems in the matching process, such as the low efficiency and mismatching. In order to improve the matching efficiency, this algorithm firstly simulates image distortion based on the position and orientation system (POS) information from real-time UAV measurements to reduce the number of simulated images. Then, the scale-invariant feature transform (SIFT) algorithm is used for feature point detection, and the extracted feature points are combined with the binary robust invariant scalable keypoints (BRISK) descriptor to generate the binary feature descriptor, which is matched using the Hamming distance. Finally, in order to improve the matching accuracy of the UAV images, based on the random sample consensus (RANSAC) a false matching eliminated algorithm is proposed. Through four groups of experiments, the proposed algorithm is compared with the SIFT and asift. The results show that the algorithm can optimize the matching effect and improve the matching speed.
Image matching is a key issue in Vision-Based UAV navigation *** paper presents an affine and rotation-invariant SIFT features descriptor for matching UAV image with satellite *** SIFT and asift algorithm are nowadays...
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ISBN:
(纸本)9781479946983
Image matching is a key issue in Vision-Based UAV navigation *** paper presents an affine and rotation-invariant SIFT features descriptor for matching UAV image with satellite *** SIFT and asift algorithm are nowadays widely applied for robust image matching,but it also has a high computational *** is used for real-time UAV position estimation but is not satisfied for affine *** introduce the new SIFT feature descriptor based on pie chart *** descriptor is invariant for rotation,affine,scale and the dimension of the feature vector is relatively ***,this method satisfies robustness and low computational *** show that this method can improve the matching accuracy and robustness.
Panoramic photography is becoming a very popular and commonly available feature in the mobile handheld devices nowadays. In traditional panoramic photography, the human structure often becomes messy if the human chang...
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Panoramic photography is becoming a very popular and commonly available feature in the mobile handheld devices nowadays. In traditional panoramic photography, the human structure often becomes messy if the human changes position in the scene or during the combination step of the human structure and natural background. In this paper, we present an effective method in panorama creation to maintain the main structure of human in the panorama. In the proposed method, we use an automatic method of feature matching, and the energy map of seam carving is used to avoid the overlapping of human with the natural background. The contributions of this proposal include automated panoramic creation method and it solves the human ghost generation problem in panorama by maintaining the structure of human by energy map. Experimental results prove that the proposed system can be effectively used to compose panoramic photographs and maintain human structure in panorama.
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