书目名称 | Optimisation Algorithms for Hand Posture Estimation | 编辑 | Shahrzad Saremi,Seyedali Mirjalili | 视频video | | 概述 | Proposes a new 3D hand model with simple shapes and low computational complexity.Demonstrates improved particle swarm optimization and multi-objective particle swarm optimization.Based on case studies | 丛书名称 | Algorithms for Intelligent Systems | 图书封面 |  | 描述 | This book reviews the literature on hand posture estimation using generative methods, identifying the current gaps, such as sensitivity to hand shapes, sensitivity to a good initial posture, difficult hand posture recovery in cases of loss in tracking, and lack of addressing multiple objectives to maximize accuracy and minimize computational cost. To fill these gaps, it proposes a new 3D hand model that combines the best features of the current 3D hand models in the literature. It also discusses the development of a hand shape optimization technique. To find the global optimum for the single-objective problem formulated, it improves and applies particle swarm optimization (PSO), one of the most highly regarded optimization algorithms and one that is used successfully in both science and industry. After formulating the problem, multi-objective particle swarm optimization (MOPSO) is employed to estimate the Pareto optimal front as the solution for this bi-objective problem. The book alsodemonstrates the effectiveness of the improved PSO in hand posture recovery in cases of tracking loss. Lastly, the book examines the formulation of hand posture estimation as a bi-objective problem fo | 出版日期 | Book 2020 | 关键词 | Hand Posture Estimation; Particle Swarm Optimization; Multi-objective Particle Swarm Optimization; Hand | 版次 | 1 | doi | https://doi.org/10.1007/978-981-13-9757-8 | isbn_softcover | 978-981-13-9759-2 | isbn_ebook | 978-981-13-9757-8Series ISSN 2524-7565 Series E-ISSN 2524-7573 | issn_series | 2524-7565 | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
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