dc.contributor.advisor | Blumenstein, Michael | |
dc.contributor.author | Green, Steven Paul | |
dc.date.accessioned | 2018-01-23T02:31:54Z | |
dc.date.available | 2018-01-23T02:31:54Z | |
dc.date.issued | 2011 | |
dc.identifier.doi | 10.25904/1912/2178 | |
dc.identifier.uri | http://hdl.handle.net/10072/366650 | |
dc.description.abstract | Object detection in complex scenes plays an important role in many real world
applications, such as scene analysis, security, traffic violation detection, and medical
research. The Object Detection and Behaviour Classification (ODBC) system
created from this PhD research, is ground-breaking and concentrates solely on the
domain of people and behaviour detection in low resolution beach scene imagery.
The video source for this research was obtained from Coastalwatch beach webcams,
which are located throughout Australia. Current object detection systems,
overall, utilise a similar methodology, following four main image processing procedures;
1) remove unwanted noise, 2) background extraction from an image scene, 3)
segmentation of the objects from the scene, and 4) object classification into different
class types. To my knowledge, there is no other past or current research studying
behaviour detection in low resolution beach imagery, and therefore, my research
leads the way in this domain.
Information from beach imagery can provide important data for tourism promotions
and beach safety. Analysis of people behaviour could assist in making
decisions about promotions and beach amenities. Automated beach systems may
provide constant monitoring of a beach, by detecting people entering the ocean in
a flagged or non-flagged area of a beach. This may also provide an early warning
system to assist lifeguards in protecting swimmers in a beach area. | |
dc.language | English | |
dc.publisher | Griffith University | |
dc.publisher.place | Brisbane | |
dc.rights.copyright | The author owns the copyright in this thesis, unless stated otherwise. | |
dc.subject.keywords | Object detection | |
dc.subject.keywords | Coastalwatch beach web-cams | |
dc.subject.keywords | Beach safety | |
dc.subject.keywords | Early warning systems | |
dc.subject.keywords | Modified direction feature | |
dc.title | Intelligent Person Behaviour Analysis in Low Resolution Beach Video Imagery | |
dc.type | Griffith thesis | |
gro.faculty | Science, Environment, Engineering and Technology | |
gro.rights.copyright | The author owns the copyright in this thesis, unless stated otherwise. | |
gro.hasfulltext | Full Text | |
dc.contributor.otheradvisor | Gao, Yongsheng | |
dc.contributor.otheradvisor | Verma, Brijesh | |
dc.rights.accessRights | Public | |
gro.identifier.gurtID | gu1336709642953 | |
gro.source.ADTshelfno | ADT0 | |
gro.source.GURTshelfno | GURT1179 | |
gro.thesis.degreelevel | Thesis (PhD Doctorate) | |
gro.thesis.degreeprogram | Doctor of Philosophy (PhD) | |
gro.department | School of Information and Communication Technology | |
gro.griffith.author | Green, Steven | |