Papers › Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object Tracking

Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object Tracking

22 Feb 2023arXiv:2302.11458archive 2025-07-28

Manuel Stoiber, Mariam Elsayed, Anne E. Reichert, Florian Steidle, Dongheui Lee, Rudolph Triebel

In many applications of advanced robotic manipulation, six degrees of freedom (6DoF) object pose estimates are continuously required. In this work, we develop a multi-modality tracker that fuses information from visual appearance and geometry to estimate object poses. The algorithm extends our previous method ICG, which uses geometry, to additionally consider surface appearance. In general, object surfaces contain local characteristics from text, graphics, and patterns, as well as global differences from distinct materials and colors. To incorporate this visual information, two modalities are developed. For local characteristics, keypoint features are used to minimize distances between points from keyframes and the current image. For global differences, a novel region approach is developed that considers multiple regions on the object surface. In addition, it allows the modeling of external geometries. Experiments on the YCB-Video and OPT datasets demonstrate that our approach ICG+ performs best on both datasets, outperforming both conventional and deep learning-based methods. At the same time, the algorithm is highly efficient and runs at more than 300 Hz. The source code of our tracker is publicly available.

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Code

dlr-rm/3dobjecttracking officialmentioned in paper report

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Tasks

3D Object Tracking6D Pose Estimation6D Pose Estimation using RGBDObjectObject Tracking

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
6D Pose Estimation OPT ICG+ AUC 17.57 #1 of 2 Archive leaderboard report
6D Pose Estimation YCB-Video ICG+ ADDS AUC 97.9 #1 of 10 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

OPT

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