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    Efficient subwindow search with submodular score functions

    Access Status
    Fulltext not available
    Authors
    An, Senjian
    Peursum, Patrick
    Liu, Wanquan
    Venkatesh, Svetha
    Date
    2011
    Type
    Conference Paper
    
    Metadata
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    Citation
    An, S. and Peursum, P. and Liu, Wanquan and Venkatesh, S. 2011. Efficient subwindow search with submodular score functions, Computer Vision and Pattern Recognition (CVPR) 2011, Jun 20 2011, pp. 1409-1416. Colorado Springs, USA: IEEE
    Source Title
    CVPR 2011
    Source Conference
    CVPR 2011
    DOI
    10.1109/CVPR.2011.5995355
    School
    Department of Computing
    URI
    http://hdl.handle.net/20.500.11937/10983
    Collection
    • Curtin Research Publications
    Abstract

    Subwindow search aims to find the optimal subimage which maximizes the score function of an object to be detected. After the development of the branch and bound (B&B) method called Efficient Subwindow Search (ESS), several algorithms (IESS, AESS, ARCS) have been proposed to improve the performance of ESS. For n×n images, IESS's time complexity is bounded by O(n3) which is better than ESS, but only applicable to linear score functions. Other work shows that Monge properties can hold in subwindow search and can be used to speed up the search to O(n3), but only applies to certain types of score functions. In this paper we explore the connection between submodular functions and the Monge property, and prove that sub-modular score functions can be used to achieve O(n3) time complexity for object detection. The time complexity can be further improved to be sub-cubic by applying B&B methods on row interval only, when the score function has a multivariate submodular bound function. Conditions for sub-modularity of common non-linear score functions and multivariate submodularity of their bound functions are also provided, and experiments are provided to compare the proposed approach against ESS and ARCS for object detection with some nonlinear score functions.

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    • Efficient algorithms for subwindow search in object detection and localization
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      Recently, a simple yet powerful branch-and-bound method called Efficient Subwindow Search (ESS) was developed to speed up sliding window search in object detection. A major drawback of ESS is that its computational ...
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      Recently, a simple yet powerful branch-and-bound method called Efficient Subwindow Search (ESS) was developed to speed up sliding window search in object detection. A major drawback of ESS is that its computational ...
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      An, Senjian; Peursum, Patrick; Liu, Wan-quan; Venkatesh, Svetha; Chen, Xiaoming (2010)
      Optimum subwindow search for object detection aims to find a subwindow so that the contained subimage is most similar to the query object. This problem can be formulated as a four dimensional (4D) maximum entry search ...
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