Stochastic process modeling for multiple human tracking using stereo video camera

2013 ◽  
Author(s):  
Takashi Fuse ◽  
Wataru Nakanishi
Keyword(s):  
Stochastic Process ◽  
Process Modeling ◽  
Video Camera ◽  
Human Tracking ◽  
Stereo Video

Armor’s ballistic resistance simulation using stochastic process modeling

2017 ◽  
Vol 102 ◽  
pp. 140-146 ◽  
Author(s):  
Beya Tahenti ◽  
Frederik Coghe ◽  
Rachid Nasri ◽  
Marc Pirlot
Keyword(s):  
Stochastic Process ◽  
Process Modeling ◽  
Ballistic Resistance

Driver assistance functions based on stereo video camera

ATZ worldwide ◽  
2014 ◽  
Vol 116 (2) ◽  
pp. 10-15 ◽  
Author(s):  
Thomas Führer ◽  
Thomas Heger ◽  
Jörg Heckel
Keyword(s):  
Video Camera ◽  
Driver Assistance ◽  
Stereo Video

scholarly journals A stochastic approach to number of corona virus cases

2020 ◽  
Vol 16 (2) ◽  
pp. 67-83
Author(s):  
H. Ünözkan ◽  
M. Yilmaz ◽  
A.M. Dere
Keyword(s):  
Stochastic Process ◽  
Random Walk ◽  
Process Modeling ◽  
Stochastic Approach ◽  
Effective Vaccine ◽  
Virus Spread ◽  
Random Walk Process ◽  
Corona Virus ◽  
Chemical Usage ◽  
Spread Speed

AbstractThis paper introduces a stochastic approach to case numbers of a pandemic disease. By defining the stochastic process random walk process is used. Some stochastic aspects for this disease are argued before stochastic study is started. During random walk process modeling new patients, recovering patients and dead conclusions are modelled and probabilities changes in some stages. Let the structure of this study includes vanishing process as a walk step, some wave happenings like big differences about spread speed as a big step in treatment- an effective vaccine or an influential chemical usage- a second corona virus pumping with virus mutation, a second global happening which bumping virus spread are defined as stages. This study only simulates a stochastic process of corona virus effects.

scholarly journals Sensitive Analysis of Observation Model for Human Tracking Using a Stochastic Process

2014 ◽  
Vol XL-5 ◽  
pp. 445-450
Author(s):  
W. Nakanishi ◽  
T. Fuse
Keyword(s):  
Stochastic Process ◽  
Ground Truth ◽  
Basic Knowledge ◽  
Human Tracking ◽  
Posterior Distributions ◽  
Sensitive Analysis ◽  
Mean Values ◽  
Advantages And Disadvantages ◽  
A Value ◽  
Range Observation

This paper aims at obtaining basic knowledge about characteristics of observation models for human tracking method as a stochastic process. As human tracking in actual cases are complicated, we cannot always use the same observation models for every situation. Thus in most cases observation models are set empirically so far. In order to achieve an efficient choice of models and parameters, understanding some advantages and disadvantages of such models regarding to observation conditions is important. In this paper we conduct a sensitive analysis on some types of observation models. In particular, we obtain both colour and range information at a railway station. We prepare six predictive distributions as well as six models and parameters for both colour and range observation models. We calculate posterior distributions of each pattern, namely 36 patterns for both colour and range models. As a sensitive analysis we compare a value of a ground truth and an expected value of posteriors. We also compare variances of predictive and posterior distributions. Through this experimental results, we confirm our analysis method is efficient to obtain information about observation models. In fact, all models analysed are good in whole. One suggestive result is that colour models can deal with a predictive error in mean values, while range models in variances. Another is that under occlusions range models show a good performance.

scholarly journals Classification in Postural Style Based on Stochastic Process Modeling

2014 ◽  
Vol 10 (2) ◽  
Author(s):  
Christophe Denis
Keyword(s):  
Stochastic Process ◽  
Process Modeling ◽  
Process Model ◽  
Correct Classification ◽  
Reduction Step ◽  
Temporal Dynamic ◽  
Finite Dimensional ◽  
Experimental Protocols ◽  
Leave One Out ◽  
Complex Trajectories

AbstractWe address the statistical challenge of classifying subjects as hemiplegic, vestibular or normal based on complex trajectories obtained through two experimental protocols designed to evaluate potential deficits in postural control. The classification procedure involves a dimension reduction step where the complex trajectories are summarized by finite-dimensional summary measures based on a stochastic process model for a real-valued trajectory. This allows us to retrieve from the trajectories information relative to their temporal dynamic. A leave-one-out evaluation yields a 79% performance of correct classification for a total of

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