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pro vyhledávání: '"Asmar, Daniel"'
This paper presents an integrated approach to Visual SLAM, merging online sequential photometric calibration within a Hybrid direct-indirect visual SLAM (H-SLAM). Photometric calibration helps normalize pixel intensity values under different lighting
Externí odkaz:
http://arxiv.org/abs/2409.16810
Autor:
Hu, Yan Song, Abboud, Nicolas, Ali, Muhammad Qasim, Yang, Adam Srebrnjak, Elhajj, Imad, Asmar, Daniel, Chen, Yuhao, Zelek, John S.
Real-time SLAM with dense 3D mapping is computationally challenging, especially on resource-limited devices. The recent development of 3D Gaussian Splatting (3DGS) offers a promising approach for real-time dense 3D reconstruction. However, existing 3
Externí odkaz:
http://arxiv.org/abs/2409.13055
Instance segmentation is an advanced form of image segmentation which, beyond traditional segmentation, requires identifying individual instances of repeating objects in a scene. Mask R-CNN is the most common architecture for instance segmentation, a
Externí odkaz:
http://arxiv.org/abs/2407.21498
The recent success of hybrid methods in monocular odometry has led to many attempts to generalize the performance gains to hybrid monocular SLAM. However, most attempts fall short in several respects, with the most prominent issue being the need for
Externí odkaz:
http://arxiv.org/abs/2306.07363
Photometric calibration is essential to many computer vision applications. One of its key benefits is enhancing the performance of Visual SLAM, especially when it depends on a direct method for tracking, such as the standard KLT algorithm. Another ad
Externí odkaz:
http://arxiv.org/abs/2305.17673
Autor:
Antoun, Maya, Asmar, Daniel
Publikováno v:
In Digital Applications in Archaeology and Cultural Heritage September 2024 34
Publikováno v:
In Robotics and Autonomous Systems September 2024 179
In this paper, we propose and validate a Joint-Initiative Supervised Autonomy (JISA) framework for Human-Robot Interaction (HRI), in which a robot maintains a measure of its self-confidence (SC) while performing a task, and only prompts the human sup
Externí odkaz:
http://arxiv.org/abs/2109.04837
Publikováno v:
In Pattern Recognition Letters May 2024 181:30-36
In this paper, we study the value of using synthetically produced videos as training data for neural networks used for action categorization. Motivated by the fact that texture and background of a video play little to no significant roles in optical
Externí odkaz:
http://arxiv.org/abs/2001.11091