A performance evaluation of detectors and descriptors for UAV visual tracking

Author(s):  
Bruce Cowan ◽  
Nursultan Imanberdiyev ◽  
Changhong Fu ◽  
Yiqun Dong ◽  
Erdal Kayacan
Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1337
Author(s):  
Kai Yit Kok ◽  
Parvathy Rajendran

Despite years of work, a robust, widely applicable generic “symmetry detector” that can paral-lel other kinds of computer vision/image processing tools for the more basic structural charac-teristics, such as a “edge” or “corner” detector, remains a computational challenge. A new symmetry feature detector with a descriptor is proposed in this paper, namely the Simple Robust Features (SRF) algorithm. A performance comparison is made among SRF with SRF, Speeded-up Robust Features (SURF) with SURF, Maximally Stable Extremal Regions (MSER) with SURF, Harris with Fast Retina Keypoint (FREAK), Minimum Eigenvalue with FREAK, Features from Accelerated Segment Test (FAST) with FREAK, and Binary Robust Invariant Scalable Keypoints (BRISK) with FREAK. A visual tracking dataset is used in this performance evaluation in terms of accuracy and computational cost. The results have shown that combining the SRF detector with the SRF descriptor is preferable, as it has on average the highest accuracy. Additionally, the computational cost of SRF with SRF is much lower than the others.


Waterlines ◽  
1993 ◽  
Vol 12 (2) ◽  
pp. 29-31 ◽  
Author(s):  
Vinay Pratap Singh ◽  
Malay Chaudhuri

Author(s):  
Ahmed Abdelsalam ◽  
Pier Luigi Ventre ◽  
Carmine Scarpitta ◽  
Andrea Mayer ◽  
Stefano Salsano ◽  
...  

2019 ◽  
Vol 151 ◽  
pp. 353-360 ◽  
Author(s):  
Fatma Outay ◽  
Faouzi Kamoun ◽  
Florent Kaisser ◽  
Doaa Alterri ◽  
Ansar Yasar

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