深度ガイドによる多視点露出ブラケティングを用いたHDRロボットビジョン
Depth-guided Multi-view Exposure Bracketing for HDR Robot Vision
極端な照明条件下での単一ショットHDR撮像を実現するため、多視点カメラに異なる露出を割り当て、深度情報で融合する手法DMEBを提案し、ロボット用の大規模HDRデータセットも構築した。
著者: Jinnyeong Kim, Juhyung Choi, Woohyeok Kim, Sunghyun Cho, Seung-Hwan Baek
分類: cs.CV
原文アブストラクト
Achieving reliable single-shot high dynamic range (HDR) imaging under extreme illumination conditions remains a long-standing challenge, yet no comprehensive benchmark exist for evaluating HDR perception in multi-sensor robotic systems. To fill this gap, we introduce a large-scale dataset collected via a custom robotic vision platform and an iPhone 13 Pro: 121 real-world scenes spanning modest and ultra-high dynamic range conditions, alongside 20 synthetic video sequences from the CARLA simulator. As a reference pipeline for this dataset, we propose Depth-guided Multi-view Exposure Bracketing (DMEB), a single-shot HDR method that distributes drastically different exposures across multi-view low-bit-depth cameras and fuses them via depth-guided confidence-aware fusion. Evaluations on our dataset show that DMEB establishes a strong reference point and highlight the promise of this sensor configuration for robust HDR perception in diverse multi-camera and depth sensor system.