Sökning: "Gaussian Mixture probability Hypothesis Density Filter"

Hittade 4 uppsatser innehållade orden Gaussian Mixture probability Hypothesis Density Filter.

1. 1. Anomaly detection in videosurveillance feeds

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Jonas Nordlöf; [2015]
   Nyckelord :;

   Sammanfattning : Traditional passive surveillance is proving ineffective as the number of available cameras for an operator often exceeds the operators ability to monitor them. Furthermore, monitoring surveillance cameras requires a focus that operators can only uphold for a short amount of time. LÄS MER

3. 2. The Evaluation of the Gaussian Mixture Probability Hypothesis Density Filter Applied in a Stereo Vision System

   Master-uppsats, Blekinge Tekniska Högskola/Sektionen för ingenjörsvetenskap

   Författare :Soheil Ghadami; [2011]
   Nyckelord :Gaussian Mixture probability Hypothesis Density Filter; Human Motion Tracking; Data Association; Occlusion Handling; Stereo Vision;

   Sammanfattning : In this thesis, the performance of the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter using a pair of stereo vision system to overcome label discontinuity and robust tracking in an Intelligent Vision Agent System (IVAS) is evaluated. This filter is widely used in multiple-target tracking applications such as surveillance, human tracking, radar, and etc. LÄS MER

4. 3. Human Motion Tracking The Gaussian Mixture Probability Hypothesis Density Filter Approach

   Master-uppsats, Blekinge Tekniska Högskola/Sektionen för ingenjörsvetenskap

   Författare :Emmanuel- Adebomi OYEKANLU; Samuel-Olusayo ONIDARE; [2010]
   Nyckelord :Probability Hypothesis Density filter; GM-PHD; IVAS; Performance Evaluation; Tracking;

   Sammanfattning : Motion tracking is an important part of the Intelligent Vision Agent System, IVAS. In this thesis, the Gaussian mixture approximation of the Probability Hypothesis Density filter (GM-PHD) was implemented to provide a reliable and computationally efficient multiple human tracker in the activity space of the IVAS. LÄS MER

5. 4. Birth Density Modeling in Multi-target Tracking Using the Gaussian Mixture PHD Filter

   Master-uppsats, Blekinge Tekniska Högskola/Avdelningen för signalbehandling

   Författare :Rongrong Chen; Min Zhu; [2008]
   Nyckelord :tracking; Gaussian Mixture PHD filter; birth density;

   Sammanfattning : A recently established method for multi-target tracking which both estimates the time-varying number of targets and their states from a sequence of observation sets in the presence of data association uncertainty, detection uncertainty, noise and false alarms is the probability hypothesis density (PHD) recursion. The approach involves modeling the respective collections of targets and measurements as random finite sets and to propagate the posterior intensity, which is a first order statistic of the random finite set of targets, in time. LÄS MER