Sentence examples for motion and aspect from inspiring English sources

Both algorithms are original with respect to the previous particle filtering-based tracking algorithm that we proposed in [4], where the problem of joint detection and tracking with coupled motion and aspect models was not considered.

Following a sequential importance sampling (SIS) [14] approach, the particles may be drawn recursively from the coupled prior statistical model for target motion and aspect, while their respective weights may be updated recursively using a likelihood function that takes into account the models for the target's signature and for the background clutter.

The integrated joint detector/tracker presented in Section 3 outperforms, however, the decoupled single-frame detector discussed in this remark by fully incorporating the dynamic motion and aspect motion into the detection process and enabling multiframe detection within the context of a track-before-detect philosophy.

The algorithms in [5 7] were however limited by the need to use discrete-valued stochastic models for both target motion and target aspect changes, with the "absent target" hypothesis treated as an additional dummy aspect state.

However, the particle filter algorithm in [4] enabled tracking only (assuming that the target was always present in all frames) and used decoupled statistically independent models for target motion and target aspect.

Two experiments addressed the motion and the form aspect of the spatio-temporal interpolation mechanism individually.

Bellos's enthusiasm carries us along, gradually introducing the branch of mathematics that enables scientists to deal with motion and many other aspects of material reality.

Continue until the dog is comfortable with both motion and the visual aspects.

The proposed algorithm enables integrated, multiframe target detection and tracking incorporating the statistical models for target motion, target aspect, and spatial correlation of the background clutter.

Furthermore, displacement kinematics are only one aspect of segmental motion (and may not be the most important aspect).

Unlike the traditional contact/association approach found in the literature, the proposed methodology enables integrated, multiframe target detection and tracking incorporating the statistical models for target aspect, target motion, and background clutter.