Results 361 to 370 of about 3,909,906 (397)

Feature extraction and terrain matching

Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition, 2003
An algorithm is presented which uses Gaussian curvature for extracting special points on the terrain, and then uses these points for recognition of particular regions of the terrain. The Gaussian curvature is chosen because it is invariant under isometry, which includes rotation and translation.
Dmitry B. Goldgof, H. Lee, Thomas S. Huang   +2 more
openaire   +2 more sources

Integrating SIFT and CNN Feature Matching for Partial-Duplicate Image Detection

IEEE Transactions on Emerging Topics in Computational Intelligence, 2020
With the increasing popularity of various deep neural networks in the area of computational intelligence, the research attention for content-based image detection/retrieval has been shifted from the handcrafted local features such as scale invariant ...
Zhili Zhou, Q. M. J. Wu, Shaohua Wan, Wendi Sun, Xingming Sun   +4 more
semanticscholar   +1 more source

Progressive Filtering for Feature Matching

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019
In this paper, we propose a simple yet efficient method termed as Progressive Filtering for Feature Matching, which is able to establish accurate correspondences between two images of common or similar scenes. Our algorithm first grids the correspondence space and calculates a typical motion vector for each cell, and then removes false matches by ...
Jun Chen, Jiayi Ma, Xingyu Jiang
openaire   +2 more sources

Progressive Feature Matching: Incremental Graph Construction and Optimization

IEEE Transactions on Image Processing, 2020
We present a novel feature matching algorithm that systematically utilizes the geometric properties of image features such as position, scale, and orientation, in addition to the conventional descriptor vectors. In challenging scenes, in which repetitive
Sehyung Lee, Jongwoo Lim, I. Suh
semanticscholar   +1 more source

Line feature matching algorithm

SPIE Proceedings, 2007
This paper presents a line feature matching algorithm. Firstly, it extracts the set of line features in the image, and represents an object using attributed relational graph (ARG). By defining relation vectors between the adjacent features, the graph can describe the structural information of an object.
Cuihua Li, Taisong Jin
openaire   +2 more sources

Feature matching in growing databases

2012 19th IEEE International Conference on Image Processing, 2012
As feature-based image matching is applied to increasing larger scale problems, it becomes necessary to match features across increasingly larger databases. Current approaches are able to conduct such feature matching, but are not flexible enough to be applied to databases that may grow at runtime.
Bernardo R. Pires, Jose M. F. Moura
openaire   +2 more sources

Enhancements in robust feature matching

2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, 2008
We present in this paper a number of new enhancements to a branch-and-bound algorithm given by Mount, Netanyahu, and Le Moigne [8] for feature matching. We introduce a new distance measure, which is more robust to the presence of outliers than the previously used measure, as well as a new variant of the search algorithm and a new search strategy.
Nathan S. Netanyahu, S. Ratanasanya, David M. Mount, Tiranee Achalakul   +3 more
openaire   +2 more sources

Matching Affine Features with the SYBA Feature Descriptor

2014
Many vision-based applications require a robust feature descriptor that works well with image deformations such as compression, illumination, and blurring. It remains a challenge for a feature descriptor to work well with image deformation caused by viewpoint change.
Dah-Jye Lee, Dan Ventura, Alok Desai
openaire   +2 more sources

ERP Feature of Matching Pennies

Applied Mechanics and Materials, 2014
Game process is a complex process, the process of the game is reflected in the subject's brain waves will be in matching pannies out of the coin, so to analyze brain waves of people can study the game process, ERP is an important means of EEG studies, through the course of the game the game ERP analysis process characteristics.
Hua Bo Xiao, Zhendong Mu
openaire   +2 more sources

Detecting and matching feature points

Journal of Visual Communication and Image Representation, 2005
Abstract This paper proposes a new feature point detector which uses a wedge model to characterize corners by their orientation and angular width. This detector is compared to two popular feature point detectors: the Harris and SUSAN detectors, on the basis of some defined quality attributes.
Etienne Vincent, Robert Laganiere
openaire   +1 more source