Gabor feATure-based face recognition using supervised locality preserving projection
標(biāo)簽： feATure-based recognition preserving projection
上傳時間： 2017-09-04
上傳用戶：古谷仁美
feature based eye tracking docs
標(biāo)簽： tracking feature based docs
上傳時間： 2017-09-15
上傳用戶：龍飛艇
The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. The term image registration is most commonly used to denote the process of alignment of images , that is of transforming them to the common coordinate system. This is done by optimizing a similarity measure between the two images. A widely used measure is Mutual Information (MI). This method requires estimating joint histogram of the two images. Experiments are presented that demonstrate the approach. The technique is intensity-based rather than feATure-based. As a comparative assessment the performance based on normalized mutual information and cross correlation as metric have also been presented.
標(biāo)簽： present modalities existence different
上傳時間： 2017-04-03
上傳用戶：qunquan
sba, a C/C++ package for generic sparse bundle adjustment is almost invariably used as the last step of every feATure-based multiple view reconstruction vision algorithm to obtain optimal 3D structure and motion (i.e. camera matrix) parameter estimates. Provided with initial estimates, BA simultaneously refines motion and structure by minimizing the reprojection error between the observed and predicted image points.
標(biāo)簽： adjustment invariably package generic
上傳時間： 2013-12-18
上傳用戶：xsnjzljj
Accurate pose estimation plays an important role in solution of simultaneous localization and mapping (SLAM) problem, required for many robotic applications. This paper presents a new approach called R-SLAM, primarily to overcome systematic and non-systematic odometry errors which are generally caused by uneven floors, unexpected objects on the floor or wheel-slippage due to skidding or fast turns.The hybrid approach presented here combines the strengths of feature based and grid based methods to produce globally consistent high resolution maps within various types of environments.
標(biāo)簽： localization environments challenging Resilient mapping R-SLAM and in
上傳時間： 2019-09-15
上傳用戶：zhudx2007
comparison of PSO-Based Optimized feature computation for automated configutation of Multi-sensor systems
標(biāo)簽： configutation Multi-sensor computation comparison
上傳時間： 2014-01-11
上傳用戶：標(biāo)點(diǎn)符號
Feature Extraction of Infrared Target Based on Image Moment and Wavelet Energy
標(biāo)簽： Extraction Infrared Feature Wavelet
上傳時間： 2016-11-12
上傳用戶：BOBOniu
Neighborhood rough set based feature evaluation and reduction
標(biāo)簽： Neighborhood evaluation reduction feature
上傳時間： 2017-05-13
上傳用戶：songnanhua
Neighborhood rough set based feature evaluation and reduction
標(biāo)簽： Neighborhood evaluation reduction feature
上傳時間： 2013-12-19
上傳用戶：nanxia
Neighborhood rough set based feature evaluation and reduction
標(biāo)簽： Neighborhood evaluation reduction feature
上傳時間： 2017-05-13
上傳用戶：lvzhr
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