She, Ying Ying (2006) Real-time animation of walking and running using inverse kinematics. Masters thesis, Concordia University.
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Abstract
Computer animation technology is a rapidly developing topic in computer science. Realistic human motion, such as walking and running, is an important part of computer animation. However, the simulation of walking and running in articulated human figure is difficult, especially in real time simulation. Fortunately, recently, Inverse kinematics algorithms provide an approach to simulate human motion in articulated figures. In this thesis, I analyzed Jacobian based Inverse Kinematics algorithms that allow theses methods to be used as an efficient real-time inverse kinematics simulator. I describe the implementation of a human motion simulator, which mainly focuses on using inverse kinematics algorithm to simulate (wounded) walking and (wounded) running motion in an articulated body. With the assistance of inverse kinematics algorithms, the animator merely gives the desired location of certain chosen points on the body and relies on the algorithm to automatically compute a set of joint angles that satisfy the end-effectors constraints. This kinematics simulation approach can be used for real time animation in articulated figure without any motion capture data. In addition, the thesis shows that it is also possible to simulate human animation by using purely mathematical techniques without physical considerations
Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering |
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Item Type: | Thesis (Masters) |
Authors: | She, Ying Ying |
Pagination: | x, 64 leaves : ill. ; 29 cm. |
Institution: | Concordia University |
Degree Name: | M. Comp. Sc. |
Program: | Computer Science and Software Engineering |
Date: | 2006 |
Thesis Supervisor(s): | Grogono, Peter |
Identification Number: | LE 3 C66C67M 2006 S54 |
ID Code: | 8919 |
Deposited By: | Concordia University Library |
Deposited On: | 18 Aug 2011 18:39 |
Last Modified: | 13 Jul 2020 20:05 |
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