Multi-sensor 3D object dataset for object recognition with full pose estimation

3D Object Recognition and Pose Estimation for Multiple Objects Using Multi-Prioritized RANSAC and Model Updating

We present a feature-based framework that combines spatial feature clustering, guided sampling for pose generation, and model updating for 3D object recognition and pose estimation. Existing methods fails in case of repeated patterns or multiple instances of the same object, as they rely only on feature discriminability for matching and on the estimator capabilities for outlier rejection. We pr...

Learning 6D Object Pose Estimation Using 3D Object Coordinates

This work addresses the problem of estimating the 6D Pose of specific objects from a single RGB-D image. We present a flexible approach that can deal with generic objects, both textured and texture-less. The key new concept is a learned, intermediate representation in form of a dense 3D object coordinate labelling paired with a dense class labelling. We are able to show that for a common datase...

Robust Multi-hypothesis 3D Object Pose Tracking

This paper tackles the problem of 3D object pose tracking from monocular cameras. Data association is performed via a variant of the Iterative Closest Point algorithm, thus making it robust to noise and other artifacts. We re-initialise the hypothesis space based on the resulting re-projection error between hypothesised models and observed image objects. This is performed through a non-linear m...

Multi-view Object Categorization and Pose Estimation

Object and scene categorization has been a central topic of computer vision research in recent years. The problem is a highly challenging one. A single object may show tremendous variability in appearance and structure under various photometric and geometric conditions. In addition, members of the same class may differ from each other due to various degrees of intra-class variability. Recently,...

Indoor Object Recognition of 3D Kinect Dataset with RNNs