Open AccessCrowd behavior analysis using MoDTA approach
Author(s) -
C K Savitha,
D. Ramesh
Publication year - 2019
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v15.i1.pp484-494
Subject(s) - span (engineering) , tracking (education) , computer science , artificial intelligence , computer vision , filter (signal processing) , detector , particle filter , video tracking , task (project management) , object (grammar) , engineering , telecommunications , psychology , civil engineering , pedagogy , systems engineering
In order to analyze the behaviors of human, significant extent of work has been carried out in the video surveillance applications. While considering the crowded scenes, the adopted features are crafted manually which have a great side to detect anomaly. It requires prior information and is hard to extract from complex video scenes and also it involves huge computational costs. In this paper, we are proposing multi-observational detection and tracking approach (MoDTA) that is based on observational filter. The MoDTA initially acquires people location in an image, so that is can detect conviction value at pointed locations which generally increases with respect to people density. In the phase of tracking, MoDTA computes the multiple observed weight values and individual features, also advection particle is used at motion model in order to facilitate the dense scenario tracking. Coefficient of correlation is used as template detector and the function of template detector is to estimate the upcoming object. Our proposed MoDTA is compared with other existing detection and tracking methods in order to evaluate the system performance.