Motion Capture methods and systems
| Institution | Jomo Kenyatta University of Science and Technology |
| Course | Information Technol... |
| Year | 3rd Year |
| Semester | Unknown |
| Posted By | Jeff Odhiambo |
| File Type | |
| Pages | No pages found |
| File Size | 585.08 KB |
| Views | 3757 |
| Downloads | 1 |
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Description
Motion capture (mocap) refers to the process of recording the movements of objects or people, typically for use in animation, video games, film production, and biomechanics research. There are several methods and systems for capturing motion, with the most common being optical, marker-based systems and non-optical, markerless systems. In optical systems, reflective markers are placed on key points of a subject's body, and cameras track their movements, creating a digital representation of the motion. Markerless systems use cameras and advanced algorithms to analyze the movement of a subject without the need for physical markers. Other methods include electromagnetic systems, which use sensors to detect movement, and inertial systems, which rely on accelerometers and gyroscopes to measure motion. Each method has its own advantages, such as accuracy, real-time feedback, and ease of use, making them suitable for various applications across industries.
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SMA 2371: Partial Differential Equations (Complete Notes, Examples & Solutions) – JKUAT Biostatistics Year 2 Semester 2
These are comprehensive and well-organized lecture notes for SMA 2371: Partial Differential Equations (PDE) offered to BSc. Biostatistics Year 2 Semester 2 students at JKUAT. The notes are neatly arranged from lecture one to the final topics, making them ideal for class learning, revision, CAT preparation, and final examinations.
The notes include detailed explanations, worked examples, step-by-step mathematical derivations, solved exercises, and applications of Partial Differential Equations. Topics covered include:
• Review of basic concepts and partial derivatives
• Jacobians, surfaces and curves in three dimensions
• Simultaneous first-order differential equations
• Methods of solving symmetric differential equations
• Orthogonal trajectories
• Pfaffian differential equations
• Linear first-order partial differential equations
• Formation of PDEs
• Elimination of arbitrary constants and arbitrary functions
• Heat, Wave, Laplace and Poisson equations
• Separation of variables
• Fourier and Laplace Transform methods
• Numerous worked examples, tutorial questions and examination-style problems with solutions.
These notes are suitable for JKUAT students and other university students studying Mathematics, Statistics, Biostatistics, Engineering, Applied Mathematics or related courses. They are an excellent revision resource for CATs and final examinations.
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