In this work, we tackle the problem of active camera localization, which controls the camera movements actively to achieve an accurate camera pose. The past solutions are mostly based on Markov Localization, which reduces the position-wise camera uncertainty for localization. These approaches localize the camera in the discrete pose space and are agnostic to the localization-driven scene property, which restricts the camera pose accuracy in the coarse scale. We propose to overcome these limitations via a novel active camera localization algorithm, composed of a passive and an active localization module. The former optimizes the camera pose in the continuous pose space by establishing point-wise camera-world correspondences. The latter explicitly models the scene and camera uncertainty components to plan the right path for accurate camera pose estimation. We validate our algorithm on the challenging localization scenarios from both synthetic and scanned real-world indoor scenes. Experimental results demonstrate that our algorithm outperforms both the state-of-the-art Markov Localization based approach and other compared approaches on the fine-scale camera pose accuracy
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Integrated Localization and Communication in 3GPP Industrial Environments
Integrated localization and communication (ILC) will be a key enabler for providing accurate location information and high data rate in next generation networks. This paper proposes a transmission frame structure and a soft information (SI)-based localization algorithm for position-assisted communications. The proposed ILC achieves improved localization accuracy and enhanced communication rate simultaneously by accounting for the statistical characteristics of the wireless environment. Results in 3rd Generation Partnership Project (3GPP) industrial scenarios show that the SI-based localization algorithm can achieve decimeter-level accuracy. Moreover, the position-assisted communication enhances the achievable rate, especially in scenarios with high mobility.
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- Award ID(s):
- 2148251
- PAR ID:
- 10515074
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3503-4485-1
- Page Range / eLocation ID:
- 9191 to 9195
- Format(s):
- Medium: X
- Location:
- Seoul, Korea, Republic of
- Sponsoring Org:
- National Science Foundation
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