Results 161 to 170 of about 13,554 (180)

Object Detection Using Scale Invariant Feature Transform

2014
An object detection scheme using the Scale Invariant Feature Transform (SIFT) is proposed in this paper. The SIFT extracts distinctive invariant features from images and it is a useful tool for matching between different views of an object. This paper proposes how the SIFT can be used for an object detection problem, especially human detection problem.
Thao Nguyen, Eun-Ae Park, Jiho Han, Dong-Chul Park, Soo-Young Min   +4 more
openaire   +1 more source

Orthogonal design for scale invariant feature transform optimization

Journal of Electronic Imaging, 2016
To improve object recognition capabilities in applications, we used orthogonal design (OD) to choose a group of optimal parameters in the parameter space of scale invariant feature transform (SIFT). In the case of global optimization (GOP) and local optimization (LOP) objectives, our aim is to show the operation of OD on the SIFT method.
Xintao Ding, Yonglong Luo, Yunyun Yi, Biao Jie, Taochun Wang, Weixin Bian   +5 more
openaire   +1 more source

Super resolution based on scale invariant feature transform

2008 International Conference on Audio, Language and Image Processing, 2008
In this paper, SIFT (scale invariant feature transform) algorithm is used for the image registration of super resolution to ensure a more stable and accurate registration result, and thus improve the result of super-resolution which will be realized by least squares minimization.
null Zhi Yuan, null Peimin Yan, null Sheng Li   +2 more
openaire   +1 more source

Make Scale Invariant Feature Transform "Fly" with CUDA

This paper introduces an implementation of scale invariant feature transform (SIFT) algorithm with CUDA. Primary  steps  including  building the  Gaussian  pyramid  and the difference of Gaussian pyramid, identification, localization [1], and orientation  generation of key-points  are  realized  on GPU with CUDA.
Yuhong Mo, Chaoyi Tan, Chenghao Wang, Hao Qin, Yushan Dong   +4 more
openaire   +2 more sources

Scale invariant feature transform evaluation in small dataset

2015 16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), 2015
This paper investigates how we can achieve object recognition in an image by looking at some examples of training images. Scale Invariant Feature Transform (SIFT) is one proposal method to detect features in an image and then can use those features to distinguish between different objects.
openaire   +1 more source

Efficient heterogeneous face recognition using Scale Invariant Feature Transform

2014 International Conference on Circuits, Systems, Communication and Information Technology Applications (CSCITA), 2014
Face recognition includes analysis of an image and extracting its facial features which will help to discriminate it from others. Scale invariant feature transform (SIFT) to extract distinctive invariant features from images can be used to perform reliable matching.
Vrushali Purandare, K T Talele
openaire   +1 more source

Study on improved scale Invariant Feature Transform matching algorithm

2010 Second Pacific-Asia Conference on Circuits, Communications and System, 2010
False matching feature points are caused by Scale Invariant Feature Transform (SIFT) which just considers the local feature information. In order to improve the precision of matching feature points, this paper proposes a method that combines the SIFT matching, epipolar restrict and regional matching.
null Youliang Yang, null Weili Liu, null Lan Zhang   +2 more
openaire   +1 more source

GSIFT: geometric scale invariant feature transform for terrain data

SPIE Proceedings, 2006
In this work, we introduce GSIFT (Geometric Scale Invariant Terrain Feature Transform), geometric descriptors that are invariant to translation, rotation, and scaling. SIFT (Scale Invariant Feature Transform) descriptors have been found to be very successful in a variety of computer vision tasks.
Suresh K. Lodha, Yongqin Xiao
openaire   +1 more source

Scale Invariant Feature Transform Based Image Matching and Registration

2014 Fifth International Conference on Signal and Image Processing, 2014
This paper presents Image matching and registration method that is invariant to scale, rotation, translation and illumination changes. The method is named as Scale Invariant Feature Transform (SIFT). This algorithm will detect and describe image features such as contours, points, corners etc.
Heena R. Kher, Vishvjit K. Thakar
openaire   +1 more source

Scale Invariant Feature Transform with Irregular Orientation Histogram Binning

2009
The SIFT (Scale Invariant Feature Transform) descriptor is a widely used method for matching image features. However, perfect scale invariance can not be achieved in practice because of sampling artefacts, noise in the image data, and the fact that the computational effort limits the number of analyzed scale space images.
Cui, Y., Hasler, N., Thormählen, T., Seidel, H. ; https://orcid.org/0000-0002-1343-8613   +3 more
openaire   +2 more sources