The wavelet transform has proved its eeciency in removing spatial redundancy. In the framework of hybrid coding schemes, this paper studies the way to combine the wavelet transform and a block matching motion estimation technique. Diierent coding schemes are presented which diier through the data on which the motion estimation and motion compensation are respectively applied. Simulations result...

The difficulty of many robot controls tasks stems from stochasticity and partial observability coupled with highly nonlinear dynamics. We propose to approximate nonlinear system dynamics using hybrid dynamics models and extend the POMDP framework to hybrid systems. To do this, we introduce a Bayesian inference based hybrid state evolution model that can be used to develop feasible motion plans ...

Abstract Cost-effective strategies for enhancing seismic velocity models are an active research topic. The recently developed hybridization technique shows promise in improving used deterministic earthquake hazard evaluation. We augment the results of Ajala and Persaud (2021) by exploring other hybrid generated using 13 sets embedding parameters—taper widths subvolumes—and summarize their effec...

We present a novel technique for utilizing the Gaussian curvature information in 3D nonrigid motion estimation in the absence of known correspondence. Differential-geometric constraints derived in the paper allow one to estimate parameters of the local affine motion model given the values of Gaussian curvature before and after motion. These constraints can be further combined with the previousl...

Ground-motion (attenuation) relations are used to estimate strong ground motion for many engineering and seismological applications. Where strongmotion recordings are abundant, these relations are developed empirically from strong-motion recordings. Where recordings are limited, they are often developed from seismological models using stochastic and theoretical methods. However, there is a larg...

We describe an algorithm for motion planning based on expert demonstrations of a skill. In order to teach robots to perform complex object manipulation tasks that can generalize robustly to new environments, we must (1) learn a representation of the effects of a task and (2) find an optimal trajectory that will reproduce these effects in a new environment. We represent robot skills in terms of ...