This paper presents a system for the automated inference of complex mental states from observed facial expressions and head gestures in video. Head actions are identified from image-based pose estimation. Facial actions, including asymmetric ones, are extracted from motion, color and shape parameters. A multi-level dynamic Bayesian network classifier models complex mental states as a sequence o...

A current popular approach to representing time in Bayesian belief networks is through Dynamic Bayesian Networks (DBNs) (Dean & Kanazawa 1989). DBNs connect sequences of entire Bayes networks, each representing a situation at a snapshot in time. We present an alternative method for incorporating time into Bayesian belief networks that utilizes abstractions of temporal representation. This metho...

In this paper, we present a dynamic Bayesian network (DBN) approach to modeling vascularization in engineered tissues. Injuries and diseases can cause significant tissue loss to the degree where the body is unable to heal itself. Tissue engineering aims to replace the lost tissue through use of stem cells and biomaterials. For tissue cells to multiply and migrate, they need to be close to blood...

This paper proposes a new general approach based on Bayesian networks to model the human behaviour. This approach represents human behaviour with probabilistic cause-effect relations based on knowledge, but also with conditional probabilities coming either from knowledge or deduced from observations. This approach has been applied to the co-simulation of the CO2 concentration in an office coupl...

In this paper, air combat simulation data is reconstructed into a dynamic Bayesian network. It gives a compact probabilistic model that describes the progress of air combat and allows efficient computing for study of different courses of the combat. This capability is used inwhat-if type analysis that investigates the effect of different air combat situations on the air combat evolution and out...

ある与えられた画像や映像の中から「もの」を取り出 す物体検出、及びその「もの」に関する情報を提示する 物体認識は、パターン認識やコンピュータビジョンの研 究分野において非常に長い歴史を持つと共に、無数とも 言えるほどの数の研究がなされている、非常にホットな トピックの 1つである。特に、人間やその顔など、一部の 特定対象についての物体検出については、対象に関する 事前知識を有効かつ最大限に利用することで、すでに実 用に供する技術水準に到達している [1], [2]。しかし、対象 に関する制約のない一般の物体検出・認識については、対 象となる物体の種類が膨大であること、同一種類の物体 でも多様な要因により見た目が大きく変化することなど から、極めて解決が難しい問題として知られている [3]。 一方で、我々人間は、特に意識することなく日常的に、 様々な物体の検出や認識を行っている。例えば...

We propose an exemplar-based tracking framework for human contour tracking. The exemplars, i.e. the contour representatives, are used to construct a contour ensemble. The main task of contour ensemble is to generate contours to fill in the gaps in-between in the test sequences, and to supply the dynamics for updating the target contour by fast contour query. As a result, a normal dynamic Bayesi...

The state description and corresponding dynamic Bayesian network are shown in Table 1 and Figure 1. In the paper we mentioned that ms denotes the state of task i. To make this more detailed, we factorms into a tuple (m i r,m i d,m i s,m i c). The variable mr encodes the release time of task i. The variable md represents the number of steps task i can still be postponed, which can be used to enc...

A dynamic Bayesian network data fusion algorithm for estimating leaf area index using time-series data from in situ measurement to remote sensing observations Yonghua Qu a b , Yuzhen Zhang a b & Jindi Wang a b a State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, 100875...

Distinguishing an Arabic handwritten text is a hard task because the Arabic word is morphologically complex and the writing style from one model is highly variable, like the recognition of words representing the names of Tunisian cities. Actually, this is the first work based on the Dynamic Hierarchical Bayesian Network (DHBN). Its objective is to get the best model by learning the structure an...