低遅延空間データ伝送のためのリアルタイムLiDAR点群高密度化
Real-Time LiDAR Point Cloud Densification for Low-Latency Spatial Data Transmission
複数のLiDAR入力と高解像度カラー画像を組み合わせ、CNNによるジョイントバイラテラルフィルタでリアルタイムに高密度深度マップを生成する手法を提案した。
詳しい要約
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2. 先行研究と比べてどこがすごい？
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著者: Kazuhiko Murasaki, Shunsuke Konagai, Masakatsu Aoki, Taiga Yoshida, Ryuichi Tanida
分類: cs.CV, cs.RO
原文アブストラクト
To realize low-latency spatial transmission system for immersive telepresence, there are two major problems: capturing dynamic 3D scene densely and processing them in real time. LiDAR sensors capture 3D in real time, but produce sparce point clouds. Therefore, this paper presents a high-speed LiDAR point cloud densification method to generate dense 3D scene with minimal latency, addressing the need for on-the-fly depth completion while maintaining real-time performance. Our approach combines multiple LiDAR inputs with high-resolution color images and applies a joint bilateral filtering strategy implemented through a convolutional neural network architecture. Experiments demonstrate that the proposed method produces dense depth maps at full HD resolution in real time (30 fps), which is over 15x faster than a recent training-based depth completion approach. The resulting dense point clouds exhibit accurate geometry without multiview inconsistencies or ghosting artifacts.
