Abstract
This paper addresses the problem of 6D pose tracking of plane segments from point clouds acquired from a mobile camera. This is motivated by manual packing operations, where an opportunity exists to enhance performance, aiding operators with instructions based on augmented reality. The approach uses as input point clouds, by its advantages for extracting geometric information relevant to estimating the 6D pose of rigid objects. The proposed algorithm begins with a RANSAC fitting stage on the raw point cloud. It then implements strategies to compute the 2D size and 6D pose of plane segments from geometric analysis of the fitted point cloud. Redundant detections are combined using a new quality factor that predicts point cloud mapping density and allows the selection of the most accurate detection. The algorithm is designed for dynamic scenes, employing a novel particle concept in the point cloud space to track detections’ validity over time. A variant of the algorithm uses box size priors (available in most packing operations) to filter out irrelevant detections. The impact of this prior knowledge is evaluated through an experimental design that compares the performance of a plane segment tracking system, considering variations in the tracking algorithm and camera speed (onboard the packing operator). The tracking algorithm varies at two levels: algorithm (Awpk), which integrates prior knowledge of box sizes, and algorithm (Awoutpk), which assumes ignorance of box properties. Camera speed is evaluated at low and high speeds. Results indicate increments in the precision and F1-score associated with using the Awpk algorithm and consistent performance across both velocities. These results confirm the enhancement of the performance of a tracking system in a real-life and complex scenario by including previous knowledge of the elements in the scene. The proposed algorithm is limited to tracking plane segments of boxes fully supported on surfaces parallel to the ground plane and not stacked. Future works are proposed to include strategies to resolve this limitation.
Original language | English |
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Article number | 17 |
Journal | Eurasip Journal on Image and Video Processing |
Volume | 2024 |
Issue number | 1 |
Early online date | 6 Aug 2024 |
DOIs | |
Publication status | E-pub ahead of print - 6 Aug 2024 |
Acknowledgements
This work would not have been possible without the support of PSI Laboratory at Universidad del Valle and Voxar Laboratory at Universidade Federal de Pernambuco.Keywords
- 6D object detection
- Integration of size priors
- Manual packing of cargo
- Multi-object tracking
- Plane tracking
- Spatial mapping
- Visual 6D tracking
- Visual tracking on dynamic environment
ASJC Scopus subject areas
- Signal Processing
- Information Systems
- Electrical and Electronic Engineering