Title: Visual Odometric Navigation: the Generalized Feature Vector way
Authors: Bhattacharya, J.
Majumder, S.
Citation: WSCG 2010: Communication Papers Proceedings: 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision in co-operation with EUROGRAPHICS, p. 15-22.
Issue Date: 2010
Publisher: Václav Skala - UNION Agency
Document type: konferenční příspěvek
URI: http://wscg.zcu.cz/WSCG2010/Papers_2010/!_2010_Short-proceedings.pdf
ISBN: 978-80-86943-87-9
Keywords: detekce funkce;identifikace trajektorie;trasování objektu
Keywords in different language: feature detection;trajectory identification;object tracking
Abstract: One of the main challenges faced by object tracking and environment-modeling techniques is the frame-to-frame correspondence of the object of interest. False detections may lead to the tracking of wrong object thus misrepresenting information about the object location and its track. The tracking algorithm of the detected object should also be computationally inexpensive and suitable for real time applications. This paper discusses how GFV, a multidimensional entity encapsulating multiple feature parameters, can uniquely identify dominant features of an object, and increase the detection reliability due to its potential to function consistently in any kind of environment, uninfluenced by view point invariance or extrinsic factors, thus generating minimal false alarms. Further a method to determine the 3D position of the object is presented which works on uncalibrated camera images and can be successfully applied to online processes. Experimental analysis using a outdoor mobile robot have been carried out to establish the competence of the algorithm. A statistical approach to reject outlier data, if any, is applied while generating the trajectory of the mobile robot used for experiments.
Rights: © Václav Skala - UNION Agency
Appears in Collections:WSCG 2010: Communication Papers Proceedings

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