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    Use of multiple low level features to find interesting regions

    237559_237559.pdf (1.325Mb)
    Access Status
    Open access
    Authors
    Borck, M.
    West, Geoff
    Tan, T.
    Date
    2014
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Borck, M. and West, G. and Tan, T. 2014. Use of multiple low level features to find interesting regions, in Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods, Mar 6-8 2014, pp. 654-661. Loire Valley, France: ICPRAM.
    Source Title
    ICPRAM 2014 - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods
    ISBN
    9789897580185
    School
    Department of Spatial Sciences
    Remarks

    Published with permission

    URI
    http://hdl.handle.net/20.500.11937/8999
    Collection
    • Curtin Research Publications
    Abstract

    Vehicle-based mobile mapping systems capture co-registered imagery and 3D point cloud information over hundreds of kilometres of transport corridor. Methods for extracting information from these large datasets are labour intensive and automatic methods are desired. In addition, such methods need to be easily configured by non-expert users to detect and measure many classes of objects. This paper describes a workflow to take a large number of image and depth features, use machine learning to generate an object detection system that is fast to configure and run. The output is high detection of the objects of interest but with an acceptable number of false alarms. This is desirable as the output is fed into a more complex and hence more computationally expensive analysis system to reject the false alarms and measure the remaining objects. Image and depth features from bounding boxes around objects of interest and random background are used for training with some popular learning algorithms. The interface allows a non-expert user to observe the performance and make modifications to improve the performance. Copyright © 2014 SCITEPRESS.

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