π-BA：共同観測最適化による組込みFPGA上のバンドル調整高速化
PI-BA Bundle Adjustment Acceleration on Embedded FPGAs with Co-observation Optimization
全点が全画像に写るわけではないという観察に基づく共同観測最適化を組み込み、FPGA-SoC上でハードウェア・ソフトウェア協調設計したバンドル調整エンジンを提案し、性能と消費電力で既存ソフト実装を上回ることを示した。
著者: Shuzhen Qin, Qiang Liu, Bo Yu, Shaoshan Liu
分類: eess.IV, cs.RO
原文アブストラクト
Bundle adjustment (BA) is a fundamental optimization technique used in many crucial applications, including 3D scene reconstruction, robotic localization, camera calibration, autonomous driving, space exploration, street view map generation etc. Essentially, BA is a joint non-linear optimization problem, and one which can consume a significant amount of time and power, especially for large optimization problems. Previous approaches of optimizing BA performance heavily rely on parallel processing or distributed computing, which trade higher power consumption for higher performance. In this paper we propose {\pi}-BA, the first hardware-software co-designed BA engine on an embedded FPGA-SoC that exploits custom hardware for higher performance and power efficiency. Specifically, based on our key observation that not all points appear on all images in a BA problem, we designed and implemented a Co-Observation Optimization technique to accelerate BA operations with optimized usage of memory and computation resources. Experimental results confirm that {\pi}-BA outperforms the existing software implementations in terms of performance and power consumption.
