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This paper mentioned the fingerprinting/model matching case. But I could not find an image based algorithm. Any suggestion about image based localization

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For fingerprint matching model, try working with SVM (support vector machines) algorithm, it is a based supervised learning model. For localization purpose you need to match ridges and bifurcation found in fingerprints.

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  • $\begingroup$ Can you give me an example? May be a paper or link $\endgroup$ – acs Jun 3 '15 at 21:55
  • $\begingroup$ Yeah sure i do have some content. Give me your email id, will send you the files i have. $\endgroup$ – shruti Jun 5 '15 at 5:01
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I'm not sure what you mean by "image based," but it seems like the term "model matching" is used to describe the notion of using an a-priori map of an environment to localize to.

You can build an a-priori map in many ways such as using a lidar, or using detected features from an image. Once you know this global map, your robot can use its sensor data to position itself on the global map by using localization algorithms such as a particle filter or EKF.

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  • $\begingroup$ Model matching algorithms applied on various sensor like magnetic or rf readings. I want to do it with images taken from robots $\endgroup$ – acs May 31 '15 at 17:34

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