Projects per year
This paper presents a novel object segmentation approach for highly complex indoor scenes. Our approach starts with a novel algorithm which partitions the scene into distinct regions whose boundaries accurately conform to the physical object boundaries in the scene. Next, we propose a novel perceptual grouping algorithm based on local cues (e.g., 3D proximity, co-planarity, and shape convexity) to merge these regions into object hypotheses. Our extensive experimental evaluations demonstrate that our object segmentation results are superior compared to the state-of-the-art methods.
|Number of pages||25|
|Early online date||4 Sep 2015|
|Publication status||Published - 1 Jun 2016|
FingerprintDive into the research topics of 'Unsupervised segmentation of unknown objects in complex environments'. Together they form a unique fingerprint.
Advanced 3D Computer Vision Algorithms for 'Find and Grasp' Future Robots
1/01/15 → 31/12/20
A 3D Video-based Vision system for Future Robots
1/01/11 → 31/12/15
Revocable 2D/3D Shape Based Multimodal Hand Biometrics for Personal Identification & Verification
1/01/12 → 29/06/17