2022/02/10 by Shuangfu Song, Song, Shuangfu, Junqiao Zhao +8
Computer Science · Engineering · #Advanced Image and Video Retrieval Techniques #FOS: Computer and information sciences #Robotics (cs.RO) #Robotics and Sensor-Based Localization #Video Surveillance and Tracking Methods #cs.RO
paper · pdf · doi:10.48550/arxiv.2202.04816
8 pages, 6 figures, accepted by IROS2022
openalex publication_date 2022/02/10 · arxiv created 2022/11/02 · arxiv updated 2022/11/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The scale ambiguity problem is inherently unsolvable to monocular SLAM without the metric baseline between moving cameras. In this paper, we present a novel scale estimation approach based on an object-level SLAM system. To obtain the absolute scale of the reconstructed map, we derive a nonlinear optimization method to make the scaled dimensions of objects conforming to the distribution of their sizes in the physical world, without relying on any prior information of gravity direction. We adopt the dual quadric to represent objects for its ability to fit objects compactly and accurately. In the proposed monocular object-level SLAM system, dual quadrics are fastly initialized based on constraints of 2-D detections and fitted oriented bounding box and are further optimized to provide reliable dimensions for scale estimation.