Image Processing and Analysis

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This course deals with the techniques for automated extraction of high-level information from images generated by cameras, three-dimensional surface sensors, and medical devices. Typical applications include automated construction of 3D models from video footage and detection of objects in various t…

Owen Carmichael

  • Nov 10, 2010 LATEST EPISODE
  • infrequent NEW EPISODES
  • 50m AVG DURATION
  • 20 EPISODES


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Latest episodes from Image Processing and Analysis

Medical Image Acquisition

Play Episode Listen Later Nov 10, 2010 44:34


Lecture 20: Carmichael discusses three main ways of obtaining medical imaging data: CT (Computed Tomography) scans, MRIs (Magnetic Resonance Imaging) and PET (Positron Emission Tomography)

Object Detection from Range Data

Play Episode Listen Later Nov 8, 2010 51:28


Lecture 19: Carmichael discusses some problems that can arise in range data-based detection and how these problems can be fixed by creating transformation-consistent clusters.

Local Shape Representations

Play Episode Listen Later Nov 5, 2010 51:42


Lecture 18: Carmichael discusses advantages of local shape representations and two methods for creating them: the segmentation method and the vertex-based method.

Global Shape Representations

Play Episode Listen Later Nov 3, 2010 55:05


Lecture 17: The instructor discusses ways of storing and searching 3D models. Explains database querying, geons, object signatures and shape histograms.

Combining Multiple Meshes

Play Episode Listen Later Oct 29, 2010 50:54


Lecture 16: Carmichael discusses two approaches (mesh-based and volumetric) for combining multiple meshes to form a single closed surface.

Mesh Alignment II

Play Episode Listen Later Oct 27, 2010 51:27


Lecture 15: In the second lecture on mesh alignment, Carmichale explains nonrigid alignment and how to accomplish this process using a technique called deformable registration.

Mesh Alignment I

Play Episode Listen Later Oct 25, 2010 51:27


Lecture 14: In the first of two lectures, Carmichale discusses rigid alignment of meshes as well as the metrics and transformation models involved.

Mesh Smoothing

Play Episode Listen Later Oct 22, 2010 50:29


Lecture 13: The instructor discusses using mesh smoothing to remove noise from three-dimensional data. Also includes Gaussian smoothing and mesh shrinkage.

3D Image Acquisition

Play Episode Listen Later Oct 20, 2010 53:05


Lecture 12: Carmichael explains how to obtain an image with three dimensions. The unit covers two principles for doing so: time of flight and triangulation.

Invariants

Play Episode Listen Later Oct 18, 2010 50:08


Lecture 11: Carmichale explains the use of invariants for dense and sparse matching, as well as some various kinds of invariants.

Texture Analysis

Play Episode Listen Later Oct 15, 2010 56:58


Lecture 09: Carmichael explains why it is useful to study the textures of an image and methods for detecting them in images.

Neighborhoods

Play Episode Listen Later Oct 15, 2010 33:23


Lecture 10: The instructor explains using neighborhood operations to access different pixels. Also covers implementation of a correlation filter.

Top-Down Image Segmentation

Play Episode Listen Later Oct 13, 2010 51:21


Lecture 08: The second of two methods is presented for grouping pixels in an image. The lecture covers deformable contours, parameterizations and gradient descent.

Bottom-Up Image Segmentation

Play Episode Listen Later Oct 11, 2010 41:23


Lecture 07: One method for grouping pixels in an image is presented. Carmichael discusses pairwise coherence, cluster modeling and modeling with metric spaces.

Object Detection Continued

Play Episode Listen Later Oct 8, 2010 51:04


Lecture 06: Carmichael explains how to go about detecting certain objects within an image if those objects cannot be outlined with just rectangles.

Object Detection

Play Episode Listen Later Oct 6, 2010 52:31


Lecture 05: Carmichael discusses finding certain rectangular objects within an image, and explains various methods for doing so, such as PCA (principal component analysis) and dimensionality reduction.

Saliency and Scale

Play Episode Listen Later Oct 4, 2010 51:17


Lecture 04: What it means to have a region of an image be 'salient' and the algorithms for finding such areas.

Edge and Corner Detection

Play Episode Listen Later Oct 1, 2010 53:31


Lecture 03: The lecture covers edge and corner detection using the Canny and Harris corner detector methods.

Fourier Analysis

Play Episode Listen Later Sep 27, 2010 50:22


Lecture 02: Introduction to Fourier analysis, as well as the subject of wavelets.

Course Introduction

Play Episode Listen Later Sep 24, 2010 51:37


Lecture 01: An introduction to image processing and analysis; covers image processing on a broad scope as well as course logistics.

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