Interactive Systems Engineering
CSE5323 3.0 Computer Vision This course will introduce the basic concepts in Computer Vision. Primarily a survey of current computational methods, we will begin by examining methods for measuring visual data (image based operators, edge detection, feature extraction), and low-level processes for feature aggregation (optic flow, segmentation, correspondence). Finally, we will consider some issues in “high-level” vision systems.
CSE5324 3.0 An Introduction to Robotics This course will introduce concepts in Robotics. The course will begin with a study of the mechanics of manipulators and robot platforms. Trajectory and course planning, environmental layout and sensing will be discussed. Finally, high-level concerns will be introduced. The need for real-time response and dynamic-scene analysis will be covered, and recent developments in robotics systems from an Artificial Intelligence viewpoint will be discussed.
CSE5331 3.0 An Introduction to Computer Graphics This course provides an introduction to computer graphics. The first half will cover window systems, display hardware, graphical primitives, scan conversion, two and three dimensional transformations and the mathematics of planar geometric projection. This will provide the groundwork for thinking and working in three dimensions. The second half of the course will concentrate on raster algorithms and on understanding the problems and approaches required to generate realistic looking images. Some of the topics include visible surface algorithms, modeling, shading, anti-aliasing, texture mapping, ray tracing and radiosity.
CSE5351 3.0 Human-Computer Interaction This course introduces the concepts and technology necessary to design, manage and implement interactive software. Students work in small groups and learn how to design user interfaces, how to realize them and how to evaluate the end result. Both design and evaluation are emphasized.
CSE6118 3.0 Combinatorial Optimization This course investigates the algorithmic and computational complexity aspects of combinatorial optimization problems. Optimization problem areas include: Linear, non-Linear, Convex, Integer, and Semidefinite Programming, as well as their application to specific areas such as network flow, matching, and various graph optimization problems.
CSE6221 3.0 Statistical Signal Processing Theory This course introduces theory and algorithms of stochastic signals and their applications to the real world. Discrete random variables, random vectors and stochastic processes are reviewed followed by signal processing methods used for detection, estimation and optimal filtering.
CSE6323 3.0 Advanced Topics in Computer Vision An advanced topics course in computer vision which covers selected topics in greater depth. Topics covered will vary from year to year depending on the interests of the class and instructor. Possible topics include: stereo vision, visual motion, computer audition, fast image processing algorithms, vision based mobile robots and active vision sensors, and object recognition. Prerequisites: CSE5323 3.0 Introduction to Computer Vision
CSE6325 3.0 Mobile Robot Motion Planning The focus of this course is on robot motion planning in known and unknown environments. Both theoretical (computational-geometric) models, as well as practical case studies will be covered in the course.
CSE6326 3.0 Principles of Human Perception and Performance in Human-Computer Interaction This course considers the role of human perception in human-computer interaction particularly computer generated graphics/sound and immersive virtual reality. Fundamental findings from sensory physiology and perceptual psychophysics are presented in the context of interface and display design.
CSE6327 3.0 Multimedia Communications The course introduces the coding, networking, and system technologies used in multimedia communications. In coding, compression standards including the ITU H.26X and ISO MPEGs and JPEGs are introduced. Issues involved in transmitting multimedia over ATM, wireless, and IP networks are discussed. (subject to approval)
CSE6328 3.0 Speech and Language Processing Introducing the latest technologies in speech and language processing, including speech recognition and understanding, key-word spotting, spoken language processing, speaker identification and verification, statistical machine translation, information retrieval, and other interesting topics. Prerequisites: CSE4451 3.0 or CSE4401 3.0.
CSE6329 3.0 Advanced Human-Computer Interaction This course examines advanced concepts and technologies for Human-Computer Interaction. Students will learn about advanced input and output devices (e.g., for mobile computing and/or Virtual Reality), about advanced design methods, how to implement effective interfaces, and how to perform rapid, effective iterative user tests.
CSE6330 3.0 Computational Pragmatics This course examines advanced concepts and technologies for Human-Computer Interaction. Students will learn about advanced input and output devices (e.g., for mobile computing and/or Virtual Reality), about advanced design methods, how to implement effective interfaces, and how to perform rapid, effective iterative user tests.
CSE6331 3.0 Advanced Image Synthesis This course concentrates on raster algorithms for image synthesis. Some of the topics may include visible surface algorithms, modelling, shading, global illumination, anti-aliasing, and texture mapping. Prerequisites: CSE5331 3.0 Introduction to Computer Graphics.
CSE6332 3.0 Statistical Visual Motion Analysis A seminar course that examines statistical approaches to visual motion analysis, including 3-D structure and motion estimation, optical flow, segmentation and tracking using tools like Maximum Likelihood Estimation, Maximum A Posteriori, Least Squares and Expectation Maximization.
CSE6333 3.0 Multiple View Image Understanding This course considers how multiple images of a scene, as captured by multiple stationary cameras, single moving cameras or their combination, can be used to recover information about the viewed scene (e.g., three-dimensional layout, camera and/or scene movement). Theoretical and practical issues of calibration, correspondence/matching and interpretation will be considered. Prerequisite: CSE5323 3.0 Introduction to Computer Vision or permission of the instructor.
CSE6334 3.0 Image Sensor Technology The design of practical vision systems requires an understanding of the sensors that generate the images and their characteristics and limitations. Single-chip cameras are now challenging existing camera technologies for applications where high integration, cost-effectiveness and/or on-chip signal processing are important. This course introduces the design of electronic camera systems, including CCDs, single-chip cameras and sensors for non-visible wavelengths. The topics covered will range from the general operating principles to the complete system performance. Prerequisite: CSE5323 3.0 Introduction to Computer Vision (recommended) or permission of the instructor.
CSE6335 3.0 Topics in Virtual Reality This course considers how to present to a user a compelling illusion of being in an alternate (virtual) reality. It considers how humans perceive visual, audio, haptic and other perceptual inputs, and how technology can be used to stimulate these sense appropriately to simulate some virtual environment. Prerequisite: CSE4471 3.0 Introduction to Virtual Reality or equivalent is recommended.
CSE6351 3.0 Dynamic Systems A modern approach to the analysis and engineering applications of linear and nonlinear systems. Modeling and linearization of multi-input– multi-output dynamic physical systems. State-variable and transfer function matrices. Emphasis on linear and matrix algebra. Numerical matrix algebra and computational issues in solving systems of linear algebraic equations, singular value decomposition, eigenvalue-eigenvector and least-squares problems. Analytical and numerical solutions of systems of differential and difference equations. Structural properties of linear dynamic physical systems, including controllability, observability and stability. Canonical realizations, linear state-variable feedback controller and asymptotic observer design. Design and computer applications to electronic circuits, control engineering, dynamics and signal processing.
CSE6352 3.0 Digital Signal Processing This course addresses the mathematics, applications and implementation of the digital signal processing algorithms widely used in areas such as multimedia telecommunications and speech and image processing. Topics include discrete-time signals and systems, discrete-time Fourier transforms and Z-transforms, discrete Fourier transforms and fast Fourier transforms, digital filter design and implementation, and multi-rate signal processing. The course will include introductory discussions of 2-dimensional signal processing, linear prediction, adaptive filtering, and selected application areas.
CSE6353 3.0 Digital Image and Video Processing The course studies image processing, image understanding, and video sequence analysis. Image processing deals with deterministic and stochastic image digitization, enhancement. restoration, and reconstruction. This includes image representation, image sampling, image quantization, image transforms (e.g., DFT, DCT, Karhunen-Loeve), stochastic image models (Gauss fields, Markov random fields, AR, ARMA) and histogram modeling. Image understanding covers image multiresolution, edge detection, shape analysis, texture analysis, and recognition. This includes pyramids, wavelets, 2D shape description through contour primitives, and deformable templates (e.g., ‘snakes’). Video processing concentrates on motion analysis. This includes the motion estimation methods, e.g., optical flow and block-based methods, and motion segmentation. The course emphasizes experimenting with the application of algorithms to real images and video. Students are encouraged to apply the algorithms presented to problems in a variety of application areas, e.g., synthetic aperture radar images, medical images, entertainment video image, and video compression.
CSE6390D 3.0 Computational Model of Visual Perception
MATH6602 3.0 Stochastic Processes Description available from the York Mathematics Department.
MATH6651 3.0 Advanced Numerical Methods Description available from the York Mathematics Department.
PHYS5170 3.0 Advanced Optics Description available from the York Physics Department.