Conference Paper

Reconstruction of Image Structure in Presence of Specular Reflections

DOI: 10.1007/3-540-45404-7_8 Conference: Pattern Recognition, 23rd DAGM-Symposium, Munich, Germany, September 12-14, 2001, Proceedings
Source: DBLP

ABSTRACT This paper deals with the reconstruction of original image structure in the presence of local disturbances such as specular re∞ec- tions. It presents two novel schemes for their elimination with respect to the local image structure: an e-cient linear interpolation scheme and an iterative fllling-in approach employing anisotropic difiusion. The al- gorithms are evaluated on images of the heart surface and are suited to support tracking of natural landmarks on the beating heart.

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    • "). At specular areas, pixels can be ''repaired'' by means of an iterative extraction/interpolation process of the local image structure [19]. However, the computational cost of existing algorithms are too high to look to a real-time implementation. "
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    ABSTRACT: In this paper, the real-time segmentation of surgical instruments with color images used in minimally invasive surgery is addressed. This work has been developed in the scope of the robotized laparoscopic surgery, specifically for the detection and tracking of gray regions and accounting for images of metallic instruments inside the abdominal cavity. With this environment, the moving background due to the breathing motion, the non-uniform and time-varying lighting conditions and the presence of specularities are the main difficulties to overcome. Then, to achieve an automatic color segmentation suitable for robot control, we developed a technique based on a discriminant color feature with robustness capabilities with respect to intensity variations and specularities. We also designed an adaptive region growing with automatic region seed detection and a model-based region classification, both dedicated to laparoscopy. The foreseen application is a good training ground to evaluate the proposed technique and the effectiveness of this work has been demonstrated through experimental results with endoscopic image sequences to efficiently locate boundaries of a landmark-free needle-holder at half the video-rate.
    Real-Time Imaging 10/2005; 11:429-442. DOI:10.1016/j.rti.2005.06.008 · 2.27 Impact Factor
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    • "Furthermore, we introduce the use of the 3-D structure tensor in background modeling as a convenient tool for representing the joint distribution of x, y, and t derivatives at each pixel. The structure tensor has been applied to a variety of problems local video analysis such as road detection [8], specularity removal [2], and motion estimation [5]. This work illustrates the use of the structure tensor field as tool for representing global patterns of local motions, which may be of broader interest. "
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    ABSTRACT: Surveillance applications often capture video over long time periods; interpretation of this data is facilitated by background models that effectively represent the typical behavior in the scene. Capturing statistics of the spatio-temporal derivatives at each pixel can efficiently model surprisingly complicated motion patterns. Considering the video as a function of space and time, the mean 3D structure tensor at each pixel characterizes local image variation, the most common local motion, and whether that motion is consistent or ambiguous. Furthermore, this structure tensor field - the structure tensor at each pixel - is interpretable as a constrained Gaussian probability density function over the derivatives measured across the entire image. In scenes with multiple global motion patterns, a mixture model (of these global distributions) automatically factors background motion into a set of flow fields corresponding to the different motions. The models are developed online in real time and can adapt to changes in background motion. We demonstrate the ability to automatically discover the different motion patterns in an intersection.
    Application of Computer Vision, 2005. WACV/MOTIONS '05 Volume 1. Seventh IEEE Workshops on; 02/2005
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    ABSTRACT: Thesis (doctoral)--Techn. University, München, 2003.
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