Mr. Xin Lu Profile

Xin Lu

at Univ of Tokushima

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Proceedings Article | 17 January 2005 Paper

View interpolation and synthesis by KLT feature tracker

Xin Lu

Proceedings Volume 5675, (2005) https://doi.org/10.1117/12.587792

KEYWORDS: Image segmentation, Cameras, 3D modeling, Visual process modeling, 3D image processing, Visualization, Motion models, Detection and tracking algorithms, Data modeling, Optical tracking

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This paper proposes a novel method synthesizing a series of continuous and realistic intermediate views between a pair of reference images without 3D knowledge. The synthesizing procedure consists of four main steps: segmentation, image pre-warping, view morphing and image post-warping. By KLT tracker the feature correspondence between a pair of reference images can be found accurately and robustly. Therefore, the fundamental matrix constructed from the correspondence has enough dependability. Based on fundamental matrix, the scanlines number and coordinates can be computed in order to pre-warp the reference image. Morphing the pre-warped virtual image between the pair of reference images across the positions of the virtual view point, a series of continuous and realistic intermediate views can be constructed. By post-warping the interpolated views, the virtual images can be obtained. And they are very similar to the actual ones which can be seen in real environment. View morphing relies on the correspondence of feature exclusively. Since KLT tracker automatically builds the robust correspondence of feature, virtual images are synthesized more accurately in our method than in other previous methods. Experimental Result shows that the higher quality correspondence of feature causes a realistic visual effect in morphing.

Proceedings Article | 30 August 2002 Paper

Dynamic object tracking against cluttered background

Xin Lu, Shunichiro Oe, Toshiyuki Kashiwagi, Tao Lu

Proceedings Volume 4925, (2002) https://doi.org/10.1117/12.481561

KEYWORDS: Optical tracking, Detection and tracking algorithms, Imaging systems, Cameras, Intelligence systems, Dynamical systems, Head, Visualization, RGB color model, Control systems

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Visual tracking could be treated as target state representation and target state inference problem in an image sequence. Moreover, in cluttered and dynamic environments the better probabilities of accurate tracking depend on richer representation and more robust inference. Target state representation could be considered as color segmentation, contour detection and position mark. Target state inference could be treated as an evaluation from old states to new one in fuzzy logic at every step of an image sequence. This paper presents a special tracking system based on factored sampling model in order to resolve difficult and complicated visual tracking problem, such as a changing of target’s representation, a clutter of environments and an interaction of target and camera. This tracking system is applied to changeful target tracking by handling the related information to sample-set between every two time-steps in an image sequence and implemented in real time system at around 20Hz with 640*480 pixels image. Specially, color and position distributions of a target have been used in this system to estimate the target situation. The results show the robust, real-time system is able to track a target with enough accuracy to automatically control the camera’s pan, tilt and zoom in order to remain the object centered in the field of vision.

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