Vehicle Tracking and Distance Estimation Based on Multiple Image Features

2007 ◽  
Author(s):  
Yixin Chen ◽  
Manohar Das ◽  
Devendra Bajpai
Keyword(s):  
Distance Estimation ◽  
Image Features ◽  
Vehicle Tracking ◽  
Multiple Image

scholarly journals Different Viewpoints Image Registration for Remote Sensing Based on Multiple Image Features

2017 ◽  
Author(s):  
Kun Yang ◽  
Anning Pan ◽  
Yang Yang ◽  
Su Zhang ◽  
Sim Heng Ong
Keyword(s):  
Remote Sensing ◽  
Image Registration ◽  
Geometric Structure ◽  
Remote Sensing Image ◽  
Image Features ◽  
Google Earth ◽  
Reference Image ◽  
Feature Descriptor ◽  
Multiple Image ◽  
Invariant Feature

Remote sensing image registration with different viewpoints plays an important role in the field of geographic information system. However, when there exists ground relief variations and imaging viewpoint changes, non-rigid distortion occurs thus the registration becomes increasingly challenging. The current methods will suffer from missing true correspondences when non-rigid geometric distortion occurs. To address the problem, we propose a robust remote sensing image registration method based on SIFT feature distance and geometric structure features. At first, the scale-invariant feature transform (SIFT), a partial intensity invariant feature descriptor is used to extract reliable feature point set from sensed and reference image respectively. Secondly, a novel algorithm based on multiple image features which constrains the geometric structure during transformation is used to estimate exact correspondences between point sets. Finally, an accurate alignment is achieved by mapping the sensed image to reference image using thin-plate spline. We evaluated the performances of the proposed method by three sets of remote sensing images obtained from the unmanned aerial vehicle (UAV) and the Google earth, and compared with five state-of-the-art methods where our algorithm solved the non-rigid registration problem of remote sensing image with different viewpoints and showed the best alignments in most cases.

scholarly journals Detection of a Hand Holding a Cellular Phone Using Multiple Image Features

2009 ◽  
pp. 151-160
Author(s):  
Hiroto Nagayoshi ◽  
Takashi Watanabe ◽  
Tatsuhiko Kagehiro ◽  
Hisao Ogata ◽  
Tsukasa Yasue ◽  
...  
Keyword(s):  
Cellular Phone ◽  
Image Features ◽  
Multiple Image

Terrain Classification using Multiple Image Features

2008 ◽  
Vol 58 (3) ◽  
pp. 353-362 ◽  
Author(s):  
Jharna Majumdar ◽  
B. Vanathy ◽  
Lekshmi S.
Keyword(s):  
Image Features ◽  
Terrain Classification ◽  
Multiple Image
Sign in / Sign up

Export Citation Format

Share Document