- 标题
- 摘要
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- 实验方案
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Practical optimal registration of terrestrial LiDAR scan pairs
摘要： Point cloud registration is a fundamental problem in 3D scanning. In this paper, we address the frequent special case of registering terrestrial LiDAR scans (or, more generally, levelled point clouds). Many current solutions still rely on the Iterative Closest Point (ICP) method or other heuristic procedures, which require good initializations to succeed and/or provide no guarantees of success. On the other hand, exact or optimal registration algorithms can compute the best possible solution without requiring initializations; however, they are currently too slow to be practical in realistic applications. Existing optimal approaches ignore the fact that in routine use the relative rotations between scans are constrained to the azimuth, via the built-in level compensation in LiDAR scanners. We propose a novel, optimal and computationally efficient registration method for this 4DOF scenario. Our approach operates on candidate 3D keypoint correspondences, and contains two main steps: (1) a deterministic selection scheme that significantly reduces the candidate correspondence set in a way that is guaranteed to preserve the optimal solution; and (2) a fast branch-and-bound (BnB) algorithm with a novel polynomial-time subroutine for 1D rotation search, that quickly finds the optimal alignment for the reduced set. We demonstrate the practicality of our method on realistic point clouds from multiple LiDAR surveys.
关键词： Branch-and-bound,Exact optimization,Point cloud registration
更新于2025-09-23 15:23:52
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[ACM Press the 3rd International Conference - Seoul, Republic of Korea (2018.08.22-2018.08.24)] Proceedings of the 3rd International Conference on Biomedical Signal and Image Processing - ICBIP '18 - Automatic Detection of Cell Regions in Microscope Images Based on BFED Algorithm
摘要： Circulating tumor cells (CTC) attract attention as a biomarker that can evaluate cancer metastasis and therapeutic effects. The CTC exists in the blood of cancer patients, so pathologists analyze blood by using a fluorescence microscope. However, manual analysis by pathologists is hard-work since the number of CTC to substances contained in the blood is very few and the cell regions are often unclear depending on shooting environments. In addition, there are few studies on automatic identification of CTC. In this paper, we develop an automatic detection method of cell regions in microscope images based on bacterial foraging-based edge detection (BFED) algorithm to analyze CTC. In the first step, we detect the initial cell regions by BFED algorithm. Second, we identify whether the region is a single cell or multiple cells come in connect with other cell(s) by SVM. Third, when a cell is connected with other one, we separate the connecting cells by branch and bound algorithm and obtain the final cell regions. We applied our proposed method to 1680 microscopy images (6 cases). The experimental results demonstrate that the proposed method has a true positive rate of 93.9% and a false positive 1.29 /case.
关键词： Saliency map,Computer aided diagnosis,Support vector machine,Branch and bound algorithm,Circulating tumor cells,BFED algorithm
更新于2025-09-23 15:22:29
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[IEEE 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) - Xiamen, China (2019.11.26-2019.11.29)] 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) - Incorporated Design of Low Side-lobe Antenna with Inclined Slots in the Narrow Wall of Rectangular Waveguide Mounted With Radome
摘要： Tremendous traf?c demands for ubiquitous access and emerging multimedia applications signi?cantly increase the energy consumption of battery-powered mobile devices. This trend leads to that energy ef?ciency (EE) becomes an essential aspect of mobile ad hoc networks (MANETs). In this paper, we explore EE optimization as measured in bits per Joule for MANETs based on the cross-layer design paradigm. We model this problem as a nonconvex mixed integer nonlinear programming (MINLP) formulation by jointly considering routing, traf?c scheduling, and power control. Because the nonconvex MINLP problem is NP-hard in general, it is exceedingly dif?cult to globally optimize this problem. We, therefore, devise a customized branch and bound (BB) algorithm to ef?ciently solve this globally optimal problem. The novelties of our proposed BB algorithm include upper and lower bounding schemes and branching rule that are designed using the characteristics of the nonconvex MINLP problem. We demonstrate the ef?ciency of our proposed BB algorithm by offering numerical comparisons with a reference algorithm that uses the relaxation manners proposed in [1]–[3]. Numerical results show that our proposed BB algorithm scheme, respectively, decreases the optimality gap 81.98% and increases the best feasible solution 32.79% compared with the reference algorithm. Furthermore, our results not only provide insights into the design of EE maximization algorithms for MANETs by employing cooperations between different layers but also serve as performance benchmarks for distributed protocols developed for real-world applications.
关键词： Energy ef?ciency,branch and bound,MANET,optimization,cross layer
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - The New European Renewable Energy Directive - Opportunities and Challenges for Photovoltaics
摘要： Tremendous traffic demands for ubiquitous access and emerging multimedia applications significantly increase the energy consumption of battery-powered mobile devices. This trend leads to that energy efficiency (EE) becomes an essential aspect of mobile ad hoc networks (MANETs). In this paper, we explore EE optimization as measured in bits per Joule for MANETs based on the cross-layer design paradigm. We model this problem as a nonconvex mixed integer nonlinear programming (MINLP) formulation by jointly considering routing, traffic scheduling, and power control. Because the nonconvex MINLP problem is NP-hard in general, it is exceedingly difficult to globally optimize this problem. We, therefore, devise a customized branch and bound (BB) algorithm to efficiently solve this globally optimal problem. The novelties of our proposed BB algorithm include upper and lower bounding schemes and branching rule that are designed using the characteristics of the nonconvex MINLP problem. We demonstrate the efficiency of our proposed BB algorithm by offering numerical comparisons with a reference algorithm that uses the relaxation manners proposed in [1]–[3]. Numerical results show that our proposed BB algorithm scheme, respectively, decreases the optimality gap 81.98% and increases the best feasible solution 32.79% compared with the reference algorithm. Furthermore, our results not only provide insights into the design of EE maximization algorithms for MANETs by employing cooperations between different layers but also serve as performance benchmarks for distributed protocols developed for real-world applications.
关键词： cross layer,branch and bound,Energy efficiency,optimization,MANET
更新于2025-09-16 10:30:52