Moving Average for Error Mitigation in Pedestrian Tracking

ISBN-13: 9786206497530 / Angielski / Miękka / 80 str.

Karin Satie Komati; Gabriel Luiz Bianchi

Opis

The Moving Average is very common in the area of time series analysis, mainly for analysing changes in stock market values. In this work, the Moving Average will be used in another context, to mitigate errors in pedestrian tracking results in video surveillance. The HOG feature extraction technique and the SVM classifier were used to detect pedestrians. For our analysis, we used the database provided by the University of Edinburgh's CAVIAR (Context Aware Vision using Image-based Active Recognition) project. The results were positive, especially when the pedestrians moved vertically in the scene in the database used.

O autorze

Karin Satie Komati has been a teacher at Ifes Campus Serra since 2012, with degrees in Computer Science and Electrical Engineering, a Master's in Computer Science and a PhD in Electrical Engineering, all from UFES. Gabriel Luiz Bianchi has a bachelor's degree in Information Systems from Ifes Campus Serra.