Physical simulation for monocular 3D model based tracking (original) (raw)
Related papers
Recent advances in monocular model-based tracking: a systematic literature review
2015
In this paper, we review the advances of monocular model-based tracking for last ten years period until 2014. In 2005, Lepetit, et. al, [19] reviewed the status of monocular model based rigid body tracking. Since then, direct 3D tracking has become quite popular research area, but monocular model-based tracking should still not be forgotten. We mainly focus on tracking, which could be applied to augmented reality, but also some other applications are covered. Given the wide subject area this paper tries to give a broad view on the research that has been conducted, giving the reader an introduction to the different disciplines that are tightly related to model-based tracking. The work has been conducted by searching through well known academic search databases in a systematic manner, and by selecting certain publications for closer examination. We analyze the results by dividing the found papers into different categories by their way of implementation. The issues which have not yet b...
Physics-based tracking of 3D objects in 2D image sequences
1994
Abstract We present a new technique for tracking 3D objects in 2D image sequences. We assume that objects are constructed from a class of volumetric part primitives. The models are initially recovered using a qualitative shape recovery process. We subsequently track the objects using local forces computed from image potentials. Therefore we avoid the expensive computation of image features.
A particle filtering framework for joint video tracking and pose estimation
2010
Abstract A method is introduced to track the object's motion and estimate its pose directly from 2-D image sequences. Scale-invariant feature transform (SIFT) is used to extract corresponding feature points from image sequences. We demonstrate that pose estimation from the corresponding feature points can be formed as a solution to Sylvester's equation. We show that the proposed approach to the solution of Sylvester's equation is equivalent to the classical SVD method for 3D-3D pose estimation.