Invariant tracking

Scale Invariant Segment Detection and Tracking

This paper presents a new feature detector that fits correctly anisotropic elongated shapes. This detector – that mixes ridges and lines detection – appears to be very robust to affine and particularly scale transformation. A tracking process, that uses the same properties than the segment detector has been studied in the aim to estimate time-to-contact from detected obstacles in an urban envir...

Color Invariant SURF in Discriminative Object Tracking

Tracking can be seen as an online learning problem, where the focus is on discriminating object from background. From this point of view, features play a key role as the tracking accuracy depends on how well the feature distinguish object and background. Current discriminative trackers use traditional features such as intensity, RGB and full body shape features. In this paper, we propose to use...

Tracking Invariant Manifolds without Differential Forms

A frequently studied problem of geometric singular perturbation theory consists in establishing the presence of trajectories of certain types (homoclinic, heteroclinic, satisfying given boundary conditions, etc.) approximating singular ones for the unperturbed problem. A useful tool for this problem has been established in Jones et al. [2] and called “Exchange Lemma” by the authors. It resemble...

Template tracking using color invariant pixel features

In our method for tracking objects, appearance features are smoothed by robust and adaptive Kalman filters, one to each pixel, making the method robust against occlusions. While the existing methods use only intensity to model the object appearance, our paper concentrates on multivalue features. Specifically, one option is to use photometric invariant color features, making the method robust to...

Invariant Surfaces and Tracking by the Hamilton