Author Type

Graduate Student

Date of Award

2007

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Marques, Oge

Abstract

Lower prices of video sensors, security concerns and the need for better and faster algorithms to extract high level information from video sequences are all factors which have stimulated research in the area of automated video surveillance systems. In the context of security the analysis of human interrelations and their environment provides hints to proactively identify anomalous behavior. However, human detection is a necessary component in systems where the automatic extraction of higher level information, such as recognizing individuals' activities, is required. The human detection problem is one of classification. In general, motion, appearance and shape are the classification approaches a system can employ to perform human detection. Techniques representative of these approaches, such us periodic motion detection, skin color detection and MPEG-7 shape descriptors are implemented in this work. An infrastructure that allows data collection for such techniques was also implemented.

Extent

114 p.

Comments

College of Engineering and Computer Science|Thesis (M.S.)--Florida Atlantic University, 2007.|FAU Electronic Theses and Dissertations Collection|College of Engineering and Computer Science

Identifier

FA00012538

Format

pdf

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