The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Scale Control for Edge Detection and Blur Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Deformable Kernels for Early Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Scale Control for Edge Detection and Blur Estimation
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Space Scale Localization, Blur, and Contour-Based Image Coding
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
ACM SIGGRAPH Computer Graphics
Image Editing in the Contour Domain
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-similarity based texture editing
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
A Robust Technique for Background Subtraction and Shadow Elimination in Traffic Video Sequence
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
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Image editing systems are essentially pixel-based. In this paper we propose a novel method for image editing in which the primitive working unit is not a pixel but an edge. The feasibility of this proposal is suggested by recent work showing that a grey-scale image can be accurately represented by its edge map if a suitable edge model and scale selection method are employed [1]. In particular, an efficient algorithm has been reported to invert such an edge representation to yield a high-fidelity reconstruction of the original image [2]. We have combined these algorithms together with an efficient method for contour grouping and an intuitive user interface to allow users to perform image editing operations directly in the contour domain. Experimental results suggest that this novel combination of vision algorithms may lead to substantial improvements in the efficiency of certain classes of image editing operations.