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IET Computer Vision

Issue 1 • Date March 2010

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Displaying Results 1 - 6 of 6
  • Shape from shading using wavelets and weighted smoothness constraints

    Publication Year: 2010, Page(s):1 - 11
    Cited by:  Papers (2)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (610 KB)

    A new method that allows capturing shapes from an input image using an optimisation-based approach is presented. An objective function is designed by introducing two terms: the first term is used to minimise the difference between the shading of the reconstructed shape and the input image, and the second term is to apply smoothness constraints to the reconstructed shape. To achieve shape reconstru... View full abstract»

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  • Hierarchical pose classification based on human physiology for behaviour analysis

    Publication Year: 2010, Page(s):12 - 24
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (911 KB)

    This study presents a new approach to classify human body poses by using angular constraints and variations of body joints. Although different classifications of the poses have been previously made, the proposed approach attempts to create a more comprehensive, accurate and extensible classification by integrating all possible poses based on angles of movement in human joints. The angular variatio... View full abstract»

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  • Gait recognition using active shape model and motion prediction

    Publication Year: 2010, Page(s):25 - 36
    Cited by:  Papers (8)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (962 KB)

    This study presents a novel, robust gait recognition algorithm for human identification from a sequence of segmented noisy silhouettes in a low-resolution video. The proposed recognition algorithm enables automatic human recognition from model-based gait cycle extraction based on the prediction-based hierarchical active shape model (ASM). The proposed algorithm overcomes drawbacks of existing work... View full abstract»

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  • Environment classification and hierarchical lane detection for structured and unstructured roads

    Publication Year: 2010, Page(s):37 - 49
    Cited by:  Papers (7)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (854 KB)

    This study presents a hierarchical lane detection system with the ability to deal with both structured and unstructured roads. The proposed system classifies the environment first before applying suitable algorithms for different types of roads. Instead of dealing with all situations with one complicated algorithm, this hierarchical architecture makes it possible to achieve high accuracy with rela... View full abstract»

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  • Spatio-temporal motion-based foreground segmentation and shadow suppression

    Publication Year: 2010, Page(s):50 - 60
    Cited by:  Papers (3)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (708 KB)

    A relevant problem in computer vision is how to detect and track moving objects from video sequences efficiently. Some algorithms require manual calibration in terms of specification of parameters or some hypotheses. A novel method is developed to extract moving objects through multi-scale wavelet transform across background subtraction. The optimal selection of threshold is automatically determin... View full abstract»

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  • Generic approach to 3D elastic model fitting to volume data

    Publication Year: 2010, Page(s):61 - 72
    Cited by:  Papers (1)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (756 KB)

    The authors address here the problem of fitting a generic model to 3D volume data and present a method that embeds the model inside a geometric block and uses the mechanical analogy of springs to fit the model to the data. The authors work out the equations that connect the deformation of the block with the deformation of the shape embedded in it and then apply the desired transformation to the bl... View full abstract»

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Aims & Scope

IET Computer Vision seeks original research papers in a wide range of areas of computer vision. The vision of the journal is to publish the highest quality research work that is relevant and topical to the field, but not forgetting those works that aim to introduce new horizons and set the agenda for future avenues of research in Computer Vision.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Majid Mirmehdi
University of Bristol
UK

Publisher
Editorial Assistant
IET Research Journals
Michael Faraday House
Six Hills Way
Stevenage  SG1 2AY  SG1 2AY  United Kingdom
iet_cvi@theiet.org