Single-Shot Clothing Category Recognition in Free-Configurations with Application to Autonomous Clothes Sorting
| Autor: | J. Paul Siebert, Li Sun, Rustam Stolkin, Simon Rogers, Gerardo Aragon-Camarasa |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
FOS: Computer and information sciences
0209 industrial biotechnology business.industry Computer science Computer Vision and Pattern Recognition (cs.CV) 010401 analytical chemistry Computer Science - Computer Vision and Pattern Recognition Sorting Pattern recognition 02 engineering and technology Clothing Autonomous robot 01 natural sciences Pipeline (software) 0104 chemical sciences Computer Science - Robotics Task (computing) 020901 industrial engineering & automation Stereopsis Feature (machine learning) Robot Artificial intelligence business Robotics (cs.RO) ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | IROS |
| ISSN: | 2153-0866 |
| Popis: | This paper proposes a single-shot approach for recognising clothing categories from 2.5D features. We propose two visual features, BSP (B-Spline Patch) and TSD (Topology Spatial Distances) for this task. The local BSP features are encoded by LLC (Locality-constrained Linear Coding) and fused with three different global features. Our visual feature is robust to deformable shapes and our approach is able to recognise the category of unknown clothing in unconstrained and random configurations. We integrated the category recognition pipeline with a stereo vision system, clothing instance detection, and dual-arm manipulators to achieve an autonomous sorting system. To verify the performance of our proposed method, we build a high-resolution RGBD clothing dataset of 50 clothing items of 5 categories sampled in random configurations (a total of 2,100 clothing samples). Experimental results show that our approach is able to reach 83.2\% accuracy while classifying clothing items which were previously unseen during training. This advances beyond the previous state-of-the-art by 36.2\%. Finally, we evaluate the proposed approach in an autonomous robot sorting system, in which the robot recognises a clothing item from an unconstrained pile, grasps it, and sorts it into a box according to its category. Our proposed sorting system achieves reasonable sorting success rates with single-shot perception. Comment: 9 pages, accepted by IROS2017 |
| Databáze: | OpenAIRE |
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