Tracking

Duration of project

18 months

Funding source

Swiss National Science Foundation

Funding number

SNSF contract nb: 200021-113827

Description

This project addressed the smoothing of tracked pose. Nonlinearities of ego motion motivate the application of particle filters (Bayesian tracking) for pose smoothing. Moreover, state-of-the-art results together with our own results on ego motion tracking directed our attention towards the problem of adaptive tuning (adaptive motion modelling). We proposed a research plan to find an accurate modelling of ego motion in order to impact on the usability of mixed reality technologies. In general, any MR application would benefit from the results envisioned in this grant. In particular, we were targeting user-centred mobile environments and we proposed to demonstrate it by developing a video-based tracking system. This system was, at a first stage, a hybrid of a marker-based and a particle filter based ego tracker. Further research was going to be pursued to change this marker-based tracker with a markerless one.

Research activities

• • Rotation-discrimnative template matching: method to perform recognition of feature points based on gradient orientation and intensity information.

• • Video-based camera tracking fusing a top-down and a bottom-up approach with a particle filter.

 

Related publications

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