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Slide 1 - Gaze Controlled Robotic Camera System Anuj Awasthi Anand Sivadasan Veeral Patel
Slide 2 - Outline Background Significance Problem Statement Concept Methodology Specific aims Budget Project Participation Time Frame
Slide 3 - Background Laparoscopic robotic surgery Eye tracker application Visual mouse Human factors Computer vision based control Face mouse Voice control
Slide 4 - Requirements in Laparoscopic Surgery Maintain the surgical point of interest in the centre of the image. Provide the required magnification of the area. Produce and maintain a horizontal image of the point of interest. Perform the preceding actions automatically, although they can be modulated by the surgeon.
Slide 5 - Visual Mouse Application Obtaining the horizontal and vertical coordinates with the eye tracker The technique of live streaming of the horizontal and vertical coordinates Interfacing of eye tracker and computer
Slide 6 - Eye Tracker System
Slide 7 - Human Factors Computer vision based control of robotic camera Camera control based on computer vision tracking of the surgical tools. Image processing used to differentiate surgical tool of interest from surroundings. No input required from the surgeon. Disadvantages Surgeon’s area of interest not taken into consideration Assumes surgical area to be surgeon’s area of interest always Surgeon ends up looking at corners of the screen often
Slide 8 - Human Factors Face Mouse control for robotic camera Image based system Tracks facial features of surgeon real time Controls camera based on pitch, yaw and roll of surgeon’s face Disadvantages Constant face movements causes strain Difficult to keep pace with movement of tools
Slide 9 - Human Factors Voice control of Robotic camera Uses voice and pedal controls Uses voice recognition techniques Set of voice commands the camera Disadvantages Considerable burden on surgeon Difficult to perform dual inputs
Slide 10 - Significance Reduction in work load on surgeon Accuracy of surgical tasks Impact on surgical time Hands Free Control
Slide 11 - Problem Statement “To develop a camera control system which reduces the work load on the surgeon without compromising on the quality of surgeon’s video display ”
Slide 12 - Concept Gaze based robotic camera Acquire gaze of the surgeon with eye tracker. Camera manipulation using eye tracker data interfaced with robot controls
Slide 13 - Robotic Hardware A small wireless 320 X 240 resolution camera with an inbuilt transmitter A Receiver Set Two Servomotors (HS 422) Links Usbor Servo Controller Pivot Post Gripper Washer, Set of Clamps, Bolts, Nuts Eye tracker System
Slide 14 - Methodology Operation site Surgeon Site
Slide 15 - Surgical Site Server System (HOST Computer) Usbor Servo Controller Visual C++ 6.0 Coding Servo Motors Robot Arm End Effecter Inverse Kinematics to be followed Wireless Camera AAA Battery supplied Receiver
Slide 16 - Surgeon’s Site Dedicated system (Client ) Image Acquisition through Internet Streaming Video Live Motion JPEG System Image Processing Intel’s Open CV Library Improve Brightness and Contrast Eye tracker System
Slide 17 - Fuzzy Based Control Pupil Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Cluster 6
Slide 18 - Fuzzy C-Means Algorithm Point of Gaze keeps fluctuating. Entire Eye tracker screen supposed to be divided into clusters. Fuzzy C-Means Algorithm used. Degree of belongingness of the point of gaze to a cluster is supposed to be the Degree of Membership of the fuzzy function Point of Gaze co-ordinates assumed to be same as co-ordinates of cluster centers.
Slide 19 - Specific Aims To cover the surgical area with camera. To obtain the point of gaze of the surgeon with eye tracker. To control the robotic camera based on the point of gaze coordinates. To facilitate Surgeon’s view.
Slide 20 - Budget
Slide 21 - Project Participation Robot Assembling : Veeral, Anuj & Anand Inverse kinematics : Anuj & Anand Software for Kinematics Control: Anuj & Veeral Interfacing Eye tracker and Robot : Anuj, Veeral & Anand Eye Tracker Output : Anand & Veeral
Slide 22 - Time Frame
Slide 23 - References M. Farid,F. Murtagh,J.L. Starck.” Computer Display Control and Interaction using Eye-Gaze". School of Computer Science ,Belfast,UK. Atsushi Nishikawa “Face Mouse : A Novel Human-Machine Interface for Controlling the Position of a Laparoscope” IEEE Transactions on Robotics and Automation,Vol. 19,No. 5 ,October 2003. Murtagh F. ”Eye Gaze Tracking System-Visual Mouse Application Development”,3rd Year Training Report ,E.N.P.S. Engineering Degree, March-August 2001.
Slide 24 - Reference (Contd..) M.E. Allaf. “Laparoscopic Visual Field – Voice vs. foot Pedal interfaces for control of AESOP Robot "Surgical Endoscopy.Feb 1998. A. Casals,J. Amat,E. Laporte. ”Automatic Guidance of an Assistant Robot in Laparoscopic Surgery” International Conference on Robotics and Automation, IEEE 1996. R. Hurteau,S. DeSantis “Laparoscopic Surgery Assisted by a Robotic Cameraman:Concept and Experimental Results”IEEE 1994.
Slide 25 - References (Contd….) George P. Mylonas,Danail Satyanov. ”Gaze Contingent Soft tissue Deformation Tracking for Minimally Invasive Robotic Surgery” MICCAI 2005, LNCS 3749, pp. 843 – 850, 2005. Shamsi T. Iqbal ,Brian P. Bailey. “Using Eye-Gaze Patterns to Identify User tasks”GHC04,2004
Slide 26 - THANK YOU!!!!!! QUESTIONS???????