Computer Science ›› 2013, Vol. 40 ›› Issue (7): 266-269.

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Novel Framework for Multi-view Object Detection through Combining Multiple Classifiers

YIN Wei-chong and LU Tong   

  • Online:2018-11-16 Published:2018-11-16

Abstract: We proposed a novel framework for detecting generic objects from arbitrary viewpoints described by varied object appearances.Our key insight is to exploit the multi-view detection patterns established by a number of detectors from different viewpoints and their relationships through the Multi-View Detector Sphere (MVDS),reflecting the underlying intrinsic structure for detecting multi-view objects.We first modeled the annotated objects from different viewpoints,and then triangulated the sphere into a number of uniformly distributed meshes to represent the explicit correspondences across view detectors.As a result,multi-view objects from untrained viewpoints can be detected by combining the outputs of the adjacent view detectors on the sphere.Our experiments on several public datasets give promising results for the experimental object classes.

Key words: Multi-view,Object detection,MVDS

[1] Thomas A,Ferrari V,Leibe B,et al.Toward multi-view object class detection[C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.New York:IEEE Computer Society,2006(2):1589-1596
[2] Viola P,Jones M.Robust Real-Time Face Detection[J].International Journal of Computer Vision,2004,57(2):137-154
[3] 武勃,黄畅,艾海舟,等.基于连续AdaBoost 算法的多视角人脸检测[J].计算机研究与发展,2005,42(9):1612-1621
[4] 徐剑,丁晓青,王生进,等.多视角多行人目标检测、定位与对应算法[J].清华大学学报:自然科学版,2009,49(8):1139-1143
[5] Savarese S,Li F.3D generic object categorization,localization and pose estimation[C]∥Proceedings of the IEEE International Conference on Computer Vision.Riode Janeiro:IEEE,2007:1-8
[6] Su H,Sun M,Li F,et al.Learning a dense multi-view representation for detection,viewpoint classification and synthesis of object categories[C]∥Proceedings of the IEEE International Conference on Computer Vision.Kyoto:IEEE,2009:213-220
[7] Liu X,Gong H,Yan S,et al.Multi-view object detection by classifier interpolation[C]∥Proceedings of the IEEE International Conference on Acoustics,Speech,and Signal Processing.Dallas:IEEE,2010:826-829
[8] Wu B,Nevatia R.Cluster Boosted Tree Classifier for Multi-View,Multi-Pose Object Detection[C]∥Proceedings of the IEEE International Conference on Computer Vision.Riode Janeiro:IEEE,2007:1-8
[9] Razavi N,Gall J,Van Gool L.Backprojection revisited:scalable multi-view object detection and similarity metrics for detections[C]∥Proceedings of 11th European Conference on Computer Vision.Heraklion:Springer,2010:620-633
[10] Friedman J,Hastie T,Tibshirani R.Additive logistic regression:a statistical view of boosting[J].The Annals of Statistics,2000,28(2):337-374
[11] Torralba A,Murphy K,Freeman W.Sharing visual features for multiclass and multiview object detection[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2007,29(5):854-869

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