Real-time sequential model-based non-rigid SFM
| Autor: | Marco Paladini, Luis M. Bergasa, Lourdes Agapito, Roberto Arroyo, Sebastián Bronte |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
0209 industrial biotechnology
business.industry Computer science 3D reconstruction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Process (computing) Robot manipulator Robotics 02 engineering and technology Object (computer science) Tracking (particle physics) 020901 industrial engineering & automation Outlier 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Noise (video) Artificial intelligence Sequential model business ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | IROS |
| Popis: | Tracking non-rigid objects from video is useful in robotic systems such as HMIs or robotic manipulator arms which interact with deformable objects. This paper proposes a method for sequential model-based 3D reconstruction of deformable objects and camera localization in real time. Non- rigid SFM methods commonly process a video sequence offline in a batch way. While there are real-time methods for rigid models, reconstruction of deformable 3D shapes for real-time applications is still unsolved. Dense approaches offer promising results, but processing all frames in batch, offline. We propose a real-time non-rigid reconstruction method based on a known deformable model. Object shape and pose is tracked by real- time estimation of camera pose and deformation coefficients. An extensive evaluation of the algorithm on several data sets, and comparison with state-of-the-art techniques is performed. The tests include different outlier rates, noise levels and occlusions handling. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|