It has been proved that acquired training is important to the development of stereopsis experience. Month-old babies already have the initial experience of invariance recognition of 3D objects. There is a slight lack of precision in the interpretation of biological vision. However, the small cost and the fast speed in calculation meet the requirements of invariance recognition, the rich visual experience in which play an important role. But what is the experience, how to acquire and how to use, these problems have never been satisfactorily resolved. In this paper we simulate the learning of visual experience in children, and solve a view angle estimated problem by using self-organizing network, which make the hidden experience clarified. Compared to the Classic camera calibration, which a large number of parameters need to be estimated, this method needs only one image and does not aim to 3D reconstruction. By avoiding the complex calibration and registration process, an amount of computation has been reduced. Visual experiences are all obtained from the most ordinary examples, and the characterization based on the geometric feature. Therefore, this method has strong expansibility and good generalization ability.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Acquiring 3D Experience of View Angle Estimation Based on Monocular and Single Image


    Contributors:
    Wei, Hui (author) / Qiu, Zhen-Yu (author)


    Publication date :

    2008-05-01


    Size :

    438010 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Monocular head pose estimation using generalized adaptive view-based appearance model

    Morency, L. P. / Whitehill, J. / Movellan, J. | British Library Online Contents | 2010



    Monocular depth estimation

    European Patent Office | 2021

    Free access

    Depth Estimation of A Monocular Image from Image Blur

    Deng, Zhonghai / Zhang, Jingyuan | British Library Conference Proceedings | 2014


    Image acquiring system, terminal, image acquiring method, and image acquiring program

    KAMADA TAKAHIRO | European Patent Office | 2019

    Free access