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Feature extraction and classification approach for the analysis of roadside video data

thesis
posted on 18.12.2017, 00:00 by Sujan ChowdhurySujan Chowdhury
The research in this thesis focused on developing an automatic video analysis approach for roadside object detection and classification. It investigated the problem of detecting roadside objects in unstructured environments. The major problem during the detection of roadside objects is the extraction of appropriate features. Successful classification of objects heavily depends on good feature representation. Learning algorithms produce low accuracy if the feature representation is poor. Hence, the main objective of this research is to develop novel feature extraction and classification techniques which can perform an accurate detection that is fast enough for real-time application.

History

Location

Central Queensland University

Additional Rights

Author retains copyright: I agree that the thesis or portfolio shall be made freely available for the purpose of research or private study

Open Access

Yes

Era Eligible

No

Supervisor

Professor Brijesh Verma ; Dr Mary Tom

Thesis Type

Doctoral Thesis