Title
Harris-SIFT descriptor for video event detection based on a machine learning approach
Date Issued
01 December 2009
Access level
metadata only access
Resource Type
conference paper
Author(s)
Araújo A.D.A.
University of Ouro Preto
Abstract
Video data is becoming increasingly important in many commercial and scientific areas with the advent of applications such as digital broadcasting, video-conferencing and multimedia processing tools, and with the development of the hardware and communications infrastructure necessary to support visual applications. The objective of this work is to propose a method for event detection in a video stream. We combine Harris-SIFT descriptor with motion information in order to detect human actions in video. We tested our method in KTH database and compared it to space-time interest points (STIP) descriptor. The results obtained achieved similar results to the STIP method. © 2009 IEEE.
Start page
153
End page
158
Language
English
OCDE Knowledge area
Ciencias de la computación
Telecomunicaciones
Scopus EID
2-s2.0-77949538537
ISBN of the container
978-076953890-7
Conference
ISM 2009 - 11th IEEE International Symposium on Multimedia - 11th IEEE International Symposium on Multimedia, ISM 2009
Sources of information:
Directorio de Producción Científica
Scopus