Parameter-free global hybrid point based range image registration

Linh Tao, Tinh Nguyen, Hiroshi Hasegawa

研究成果: Conference contribution

1 被引用数 (Scopus)


In order to tackle one of the most difficult tasks in 3D computer vision, range image registration (RIR), this paper proposes a new approach to register two range images of the same object or scenario from different scanning angles. The new method of two dimensional point based boundary searching replaces conventional six dimension methods. This point based approach is applied into hybrid registration paradigm which integrates global searching algorithms with a local alignment tool, Iterative Closest Point (ICP). With this approach, searching algorithms are able to find global optima more efficiently with significantly fewer searching dimensions. Because of using data points as searching variables and taking all of them into consideration, registration algorithms are able to explore the whole space to find the global solution without any parameter constraint. Point based searching approach is successfully implemented on hybrid registration algorithms which use state-of-the-art global searching tools including Simulated Annealing (SA), Differential Evolution (DE) and Particle Swarm Optimization (PSO). The new approach is evaluated in terms of both accuracy and robustness in various experiments on different datasets to prove its superior over the conventional approach.

ホスト出版物のタイトルProceedings of 2017 International Conference on Advances in Image Processing, ICAIP 2017
出版社Association for Computing Machinery
出版ステータスPublished - 2017 8月 25
イベント2017 International Conference on Advances in Image Processing, ICAIP 2017 - Bangkok, Thailand
継続期間: 2017 8月 252017 8月 27


名前ACM International Conference Proceeding Series
Part F131200


Other2017 International Conference on Advances in Image Processing, ICAIP 2017

ASJC Scopus subject areas

  • ソフトウェア
  • 人間とコンピュータの相互作用
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ ネットワークおよび通信


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