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CUDA and OpenMp Implementation of Boolean Matrix Product with Applications in Visual SLAM

Zarringhalam, Amir, Shiry Ghidary, Saeed, Mohades, Ali and Sadegh-Zadeh, Seyed-Ali (2023) CUDA and OpenMp Implementation of Boolean Matrix Product with Applications in Visual SLAM. Algorithms, 16 (2). p. 74. ISSN 1999-4893

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Abstract or description

In this paper, the concept of ultrametric structure is intertwined with the SLAM procedure. A set of pre-existing transformations has been used to create a new simultaneous localization and mapping (SLAM) algorithm. We have developed two new parallel algorithms that implement the time-consuming Boolean transformations of the space dissimilarity matrix. The resulting matrix is an important input to the vector quantization (VQ) step in SLAM processes. These algorithms, written in Compute Unified Device Architecture (CUDA) and Open Multi-Processing (OpenMP) pseudo-codes, make the Boolean transformation computationally feasible on a real-world-size dataset. We expect our newly introduced SLAM algorithm, ultrametric Fast Appearance Based Mapping (FABMAP), to outperform regular FABMAP2 since ultrametric spaces are more clusterable than regular Euclidean spaces. Another scope of the presented research is the development of a novel measure of ultrametricity, along with creation of Ultrametric-PAM clustering algorithm. Since current measures have computational time complexity order, O(n3) a new measure with lower time complexity, O(n2) , has a potential significance.

Item Type: Article
Uncontrolled Keywords: ultrametricity; dissimilarity spaces; Fast Appearance Based Mapping; Open Multi-Processing
Faculty: School of Digital, Technologies and Arts > Computer Science, AI and Robotics
Depositing User: Ali SADEGH ZADEH
Date Deposited: 14 Feb 2023 09:46
Last Modified: 24 Feb 2023 14:05

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