Sentence examples for tracking framework to from inspiring English sources

In this paper, we propose a novel tracking framework to handle the above tracking failures.

This knowledge is subsequently used in a particle filter tracking framework to prune those predictions which are not likely to be found in that action.

Metaxas et al. [21] employ geometric and Local Binary pattern (LBP) features on a combined 2D and 3D face tracking framework to automatically recognize linguistically significant non-manual expressions in continuous ASL videos.

Results: We developed an automated image analysis and colony tracking framework to obtain an objective and reproducible quantification of structural properties of cell colonies as they evolve in space and time.

This re-identification module is integrated within our tracking system to fuse tracklets obtained from a particle filter based tracking framework in a mono-camera tracking system.

The efficiency of the designed human body parts tracking framework is illustrated over various real-world video sequences.

In tracking framework, the particle filter-based tracker requires a similarity measurement for the purpose of calculating the likelihood between particles and the target object.

Cong et al. [8] propose a robust MCMC-based PF tracking framework, which combines a color-based observation model with detection confidence density derived from histograms of oriented gradients (HOG) descriptor, and adopts MCMC-based particle algorithm to estimate the posterior distribution of the state of a human object to solve the robust human tracking problem.

It will be shown that our objective function satisfies two critical properties that are required for this discontinuity-tracking framework to be practical: (1) possesses a local minima at a discontinuity-aligned mesh and (2) decreases monotonically to this minimum in a neighborhood of radius approximately h/2, whereas other popular discontinuity indicators fail to satisfy the latter.

To cope with this problem, Kuo et al. [54] adopt multiple instances learning (MIL) to learn an appearance affinity model, which is then integrated with the spatial-temporal information to train an improved inter-camera track association framework to tackle the target handover tasks across cameras.

In addition, TP model is convenient to build with a tracking framework and adopts sparse methods to estimate signal position.