Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

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Tracking Scissors using reflective Lines

Student: KatharinaPentenrieder
Supervisor: Dipl.Inf. Martin Bauer
Professor: Prof. Gudrun Klinker
Submission date: 15.01.2005
Student Project (Diplomarbeit)

This student project is about tracking a pair of scissors using retroreflective lines at each leg.


Color Image Infrared Image
farbe.jpg grau.jpg

Goal of the project is to track the threedimensional position of the instrument using a pair of stereo cameras. To reach this goal, the legs are covered by retroreflective material and the camera is surrounded by infrared flashlights. This results in an easily recognizable image of only the legs. Finding the lines in both camera images can be used to get the threedimensional position of the instrument. Hough Transformation can be used to search for the lines.


Detecting Lines - Hough Transformation, Pixel Elimination and Least Squares

Hough Transformation Accumulator Array
hough.jpg acc_labels.jpg

Each point of the x-y-plane is represented by a sinusoidal curve in the ρ-θ-plane. Collinear points are mapped onto curves that have a common point of intersection. Therefore lines in the x-y-plane can be detected by counting the number of intersecting curves in each point of the ρ-θ-plane. This is done via an accumulator array. The accumulator maxima represent the most likely pairs (ρ,θ) of collinear points in the original x-y-plane.

Hough Detected Lines Image after Elimination Least Squares Lines
split_2linien.jpg EliminiertePunkte1_klein.jpg LeastSquaresLinien1_klein.jpg

To find both lines the Hough Transformation is applied twice, for each line separately. After the first accumulation the pixels around the detected line are eliminated to create a new image for the second transformation. Finally the Least Squares Method is used to get an optimal result.

3D-Positioning - Camera Calibration and Line Triangulation

Camera Model Epipolar geometry
3Dcamera.jpg 3Dline.jpg

To determine the 3D-position of an object several steps are necessary. First the relationship between a world point and an image point needs to be expressed. This can be represented as x = PX where P is the camera matrix. P is retrieved via camera calibration. Secondly - given two cameras - the 3D Position of a line is determined using triangulation. C and C' are the two cameras. Their relative position is represented by a rotation matrix R and a translation vector T. Given two points on the line in each camera frame two planes can be calculated which intersect in the desired 3D line.

Tracking Lines

Line Tracking

Tracking over a series of images can either be done directly after the lines have been found via Hough Transformation or it is postponed until the 3D position of the object is determined. One method of tracking could be to move a template vector along normals of the determined line and search for an optimum of conformance with the underlying image. The template vector represents a gray value profile of the line.



Title: Tracking Scissors using reflective Lines
Abstract: Tracking plays an important role in Augmented Reality (AR) applications. In medical augmented reality tracking systems must allow to accurately determine the position of medical instruments without influencing or disturbing the surgeons working environment. Retro-reflective material combined with infrared light presents an interesting and promising method of optical tracking. This thesis analyzes the special case of tracking medical scissors using retro-reflective lines. The particular structure of this instrument permits its identification in an image only through the position of the two legs. During this project the whole process of image generation line detection camera calibration and 3D reconstruction via line triangulation was examined. The used methods problems and undertaken optimizations are presented here. Furthermore some ideas for the part of tracking the instrument over a series of images are briefly discussed.
Student: Katharina Pentenrieder
Director: Gudrun Klinker
Supervisor: Martin Bauer
Type: Diploma Thesis
Status: finished
Finish: 2005/01/15

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