Tracking objects in 3D space and predicting their 6DoF pose is an essential task in
computer vision. State-of-the-art approaches often rely on object texture to tackle this …

This paper solves the problem of real-time 6-DoF object tracking from an RGB video. Prior
optimization-based methods optimize the object pose by aligning the projected model to the …

Region-based methods have become increasingly popular for model-based, monocular 3D
tracking of texture-less objects in cluttered scenes. However, while they achieve state-of-the …

Template-based 3D object tracking still lacks a high-precision benchmark of real scenes due
to the difficulty of annotating the accurate 3D poses of real moving video objects without …

Optimization-based 3D object tracking is known to be precise and fast, but sensitive to large
inter-frame displacements. In this paper we propose a fast and effective non-local 3D …

Tracking the pose of a specific rigid object from monocular sequences is a basic problem in
computer vision. State-of-the-art methods assume motion continuity between two …

The robustness and accuracy of industrial object pose tracking is critical in manufacturing
automation. Vision-based object tracking methods estimate poses by establishing feature …

In this paper, we present a multi-object 6D detection and tracking pipeline for potentially
similar and non-textured objects. The combination of a convolutional neural network for …

Previous evaluations on 6DoF object pose tracking have presented obvious limitations
along with the development of this area. In particular, the evaluation protocols are not unified …

The reprojection process is a crucial step in 3D object tracking, which is used to obtain the
object's 3D points to optimize pose. Although multiple reprojections can significantly improve …