Modeling and Generation of Soft Data in Kinematic Scenarios for Surveillance Applications

Abstract

Recently data generation has become an important research topic. Simulated data are not expensive and can be used immediately after being generated. Unlike simulated data, real data is expensive and time consuming to collect and in many cases real world data need to be cleaned before using. In this work we have developed a software that can generate soft data from events. This software generates output of NLP without using NLP complex technique, which can be used for testing fusion algorithms or using the generated data for testing data quality, as well as data mining algorithms. All the coding part has been done in C++ using Microsoft Visual Studio.