Jiang Gao
ABSTRACT
We explore how to optimally categorize regions for faster and more reliable image matching and registration. We propose using the entropy of histogram of oriented gradients(HOG) features to characterize image regions, and propose a region-sensitive feature selection algorithm for image registration. We apply the region categorization algorithms to several mobile applications, including mobile visual search and image registration for panorama. We demonstrate the effectiveness of our approach by experimental results on a large dataset.
- H. Bay, T. Tuytelaars, and L. V. Gool. Surf: Speeded up robust features. ECCV, pages 404--417, 2006. Google Scholar
Digital Library
- M. Brown and D. G. Lowe. Recognizing panoramas. In Proceedings of the 9th International Conference on Computer Vision (ICCV), pages 1218--1225, 2003. Google ScholarDigital Library
- N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. IEEE Computer Vision and Pattern Recognition (CVPR), 1:886--893, 2005. Google ScholarDigital Library
- W. T. Freeman and M. Roth. Orientation histograms for hand gesture recognition. International Workshop on Automatic Face and Gesture Recognition, pages 296--301, 1995.Google Scholar
- J. Gao. Hybrid tracking and visual search. Proceedings of ACM SIGMM International Conference on Multimedia, pages 909--912, 2008. Google ScholarDigital Library
- R. I. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. Cambridge University Press, 2000. Google ScholarDigital Library
- T. Leung and J. Malik. Representing and recognizing the visual appearance of materials using three-dimensional textons. International Journal of Computer Vision, 43(1):29--44, June 2001. Google ScholarDigital Library
- S. C. Zhu, Y. N. Wu, and D. B. Mumford. Filters, random field and maximum entropy (frame): Towards a unified theory for texture modeling. International Journal of Computer Vision, 27(2):107--126, March 1998. Google ScholarDigital Library
Index Terms
- Region categorization with mobile applications
Recommendations
Region-based image registration for mosaicking
In this paper, a method for image registration using 2D regions as correspondence features is proposed. The proposed method consists of three stages. First, a region segmentation technique is used to find reasonably good regions in image pairs. Second, ...
Region-aware Registration for Multi-stained Histology Images
ICIGP '21: Proceedings of the 2021 4th International Conference on Image and Graphics ProcessingMulti-stained histology images can provide a wealth of pathological information for clinical diagnosis. Accurate registration of multi-stained images, especially on ROIs (e.g. tumor area), can offer a more precise and comprehensive understanding of a ...
Texture-Energy-Analysis-Based Image Recognition Algorithm for Identifying the Early Stage Tumor
CCCM '08: Proceedings of the 2008 ISECS International Colloquium on Computing, Communication, Control, and Management - Volume 01A new algorithm (Image Registration and Texture Energy Analysis ---- ITEAR), which can accurately identify the early stage tumor in CT images, is developed in this paper. The ITEAR algorithm aligns the corresponding PET and CT images by the mutual ...
Comments