Vittorio Murino | PubMed Health

PubMed2004

Investigating Hidden Markov Models' capabilities in 2D shape classification.

In this paper, Hidden Markov Models (HMMs) are investigated for the purpose of classifying planar shapes represented by their curvature coefficients. In the training phase, special attention is devoted to the initialization and model selection issues, which make the learning phase particularly effective. The results of tests on different data sets show that the proposed system is able to accurately classify objects that were translated, rotated, occluded, or deformed by shearing, also in the presence of noise.

Algorithms↗

PubMedDate not supplied

Augmented scene modeling and visualization by optical and acoustic sensor integration.

In this paper, underwater scene modeling from multisensor data is addressed. Acoustic and optical devices aboard an underwater vehicle are used to sense the environment in order to produce an output that is readily understandable even by an inexperienced operator. The main idea is to integrate multiple-sensor data by geometrically registering such data to a model. The geometrical structure of this model is a priori known but not ad hoc designed for this purpose. As a result, the vehicle pose is derived and model objects can be superimposed upon actual images, thus generating an augmented-reality representation. Results on a real underwater scene are reported, showing the effectiveness of the proposed approach.

Journal Article↗