Performance Evaluation of Image Feature Detectors and Descriptors for Outdoor-Scene Visual Navigation

Author(s):  
Dzulfahmi ◽  
Naoya Ohta
2013 ◽  
Vol 774-776 ◽  
pp. 1625-1628 ◽  
Author(s):  
Kai Hu ◽  
Wei Feng Chen ◽  
Dan Mao ◽  
Zi Chen Zheng ◽  
Jing Yi Duan

To make robot more intelligence, this paper proposed a new image feature named as ROLD-map which based on Rank-Ordered Logarithmic Difference (ROLD), and this feature enable researchers understand images complication directly and accuracy. Experimental data show that it can recognize the sky, tree and road obviously with very little time through proposed feature. It provides the fundamental analysis for improving the precision of image recognition, and also gives the reference research for improving the precision of image recognition for the process of visual navigation of robot.


2014 ◽  
Vol 287 ◽  
pp. 38-49 ◽  
Author(s):  
Dongfang Yang ◽  
Zhiguo Liu ◽  
Fuchun Sun ◽  
Jinsheng Zhang ◽  
Huaping Liu ◽  
...  

2015 ◽  
Vol 27 (4) ◽  
pp. 392-400 ◽  
Author(s):  
Keita Kurashiki ◽  
◽  
Mareus Aguilar ◽  
Sakon Soontornvanichkit

<div class=""abs_img""> <img src=""[disp_template_path]/JRM/abst-image/00270004/09.jpg"" width=""300"" /> Mobile robot with a stereo camera</div> Autonomous mobile robots has been an active research recently. In Japan, the Tsukuba Challenge is held annually since 2007 in order to realize autonomous mobile robots that coexist with human beings safely in society. Through technological incentives of such effort, laser range finder (LRF) based navigation has rapidly improved. A technical issue of these techniques is the reduction of the prior information because most of them require precise 3D model of the environment, that is poor in both maintainability and scalability. On the other hand, in spite of intensive studies on vision based navigation using cameras, no robot in the Challenge could achieve full camera navigation. In this paper, an image based control law to follow the road boundary is proposed. This method is a part of the topological navigation to reduce prior information and enhance scalability of the map. As the controller is designed based on the interaction model of the robot motion and image feature in the front image, the method is robust to the camera calibration error. The proposed controller is tested through several simulations and indoor/outdoor experiments to verify its performance and robustness. Finally, our results in Tsukuba Challenge 2014 using the proposed controller is presented. </span>


2019 ◽  
Vol 31 (2) ◽  
pp. 277-296
Author(s):  
STANLEY L. TUZNIK ◽  
PETER J. OLVER ◽  
ALLEN TANNENBAUM

Image feature points are detected as pixels which locally maximise a detector function, two commonly used examples of which are the (Euclidean) image gradient and the Harris–Stephens corner detector. A major limitation of these feature detectors is that they are only Euclidean-invariant. In this work, we demonstrate the application of a 2D equi-affine-invariant image feature point detector based on differential invariants as derived through the equivariant method of moving frames. The fundamental equi-affine differential invariants for 3D image volumes are also computed.


2016 ◽  
Vol 25 (1) ◽  
pp. 010501 ◽  
Author(s):  
Bruno Ferrarini ◽  
Shoaib Ehsan ◽  
Naveed Ur Rehman ◽  
Klaus D. McDonald-Maier

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