'X0 y0' diaporamas de présentation

Three-Dimensional Viewing

Three-Dimensional Viewing. Jehee Lee Seoul National University. Viewing Pipeline. Virtual Camera Model. Viewing Transformation The camera position and orientation is determined Projection Transformation The selected view of a 3D scene is projected onto a view plane.

1.03k views • 51 slides

Chapter 10 Image Segmentation

Chapter 10 Image Segmentation. Image segmentation divides an image into regions that are connected and have some similarity within the region and some difference between adjacent regions. The goal is usually to find individual objects in an image.

2.78k views • 51 slides

LANDMARC Indoor Location Sensing Using Active RFID

871 views • 49 slides

Chapter 6

Chapter 6. Prune-and-search. A simple example: Binary search. sorted sequence : (search 9) 1 4 5 7 9 10 12 15 step 1 ? step 2 ? step 3 ? After each comparison, a half of the data set are pruned away .

543 views • 45 slides

Earthquake Location

Earthquake Location. by Annabel Kelly. Overview. The basic principles S-P location (manual) location by inversion single station location depth assessment velocity models Relocation methods joint hypocentral location master event location Other related topics Waveform modeling

1.01k views • 41 slides

The Cricket Compass for Context-Aware Mobile Applications

The Cricket Compass for Context-Aware Mobile Applications Nissanka Priyantha, Allen Miu , Hari Balakrishnan, Seth Teller MIT Laboratory for Computer Science http://nms.lcs.mit.edu/ ? Cricket Location System Original Version [mobicom00] Location information: room, floor, building, etc.

1.05k views • 31 slides

View Morphing by Steven M. Seitz Charles R. Dyer

Comp 767: Advanced Topics in Graphics: Image-Based Rendering. View Morphing by Steven M. Seitz Charles R. Dyer. Irwin Chiu Hau Computer Science McGill University Winter 2004. Comp 767: Advanced Topics in Graphics: Image-Based Rendering. Overview. Mona Lisa view morphs

879 views • 31 slides

The Cricket Compass for Context-Aware Mobile Applications

The Cricket Compass for Context-Aware Mobile Applications. Nissanka Priyantha, Allen Miu , Hari Balakrishnan, Seth Teller MIT Laboratory for Computer Science http://nms.lcs.mit.edu/. ?. Cricket Location System. Original Version [mobicom00] Location information: room, floor, building, etc.

510 views • 31 slides

Spline Interpolation Method

Spline Interpolation Method. Major: All Engineering Majors Authors: Autar Kaw, Jai Paul http://numericalmethods.eng.usf.edu Transforming Numerical Methods Education for STEM Undergraduates. Spline Method of Interpolation http://numericalmethods.eng.usf.edu. What is Interpolation ?.

766 views • 31 slides

Spline Interpolation Method

Spline Interpolation Method. Major: All Engineering Majors Authors: Autar Kaw, Jai Paul http://numericalmethods.eng.usf.edu Transforming Numerical Methods Education for STEM Undergraduates. Spline Method of Interpolation http://numericalmethods.eng.usf.edu. What is Interpolation ?.

534 views • 31 slides

Review of Interpolation

Review of Interpolation. A method of constructing a function that crosses through a discrete set of known data points. . . Spline (general case). Given n +1 distinct knots x i such that:. with n +1 knot values y i find a spline function.

722 views • 25 slides

Static Image Mosaicing

Static Image Mosaicing. Amin Charaniya (amin@cse.ucsc.edu). EE 264: Image Processing and Reconstruction. Presentation Overview. Problem definition Background Literature Survey Image transformations Image Registration Coarse Image registration Transformation Optimization Image Blending

402 views • 22 slides

Static Image Mosaicing

Static Image Mosaicing. Amin Charaniya (amin@cse.ucsc.edu). EE 264: Image Processing and Reconstruction. Presentation Overview. Problem definition Background Literature Survey Image transformations Image Registration Coarse Image registration Transformation Optimization Image Blending

397 views • 22 slides

Absorption and Stripping

Absorption and Stripping. Some important definitions. In distillation, heat drives the separation of the more volatile from the less volatile component; this unit op is always counter-current .

3.07k views • 22 slides

Lagrangian Interpolation

Lagrangian Interpolation. Major: All Engineering Majors Authors: Autar Kaw, Jai Paul http://numericalmethods.eng.usf.edu Transforming Numerical Methods Education for STEM Undergraduates. Lagrange Method of Interpolation http://numericalmethods.eng.usf.edu. What is Interpolation ?.

464 views • 21 slides

Some Basic Relationships Between Pixels

Some Basic Relationships Between Pixels. Definitions: f(x,y): digital image Pixels: q, p Subset of pixels of f(x,y): S. Neighbors of a Pixel. A pixel p at (x,y) has 2 horizontal and 2 vertical neighbors: (x+1,y), (x-1,y), (x,y+1), (x,y-1)

1.2k views • 20 slides

Some Basic Relationships Between Pixels

Some Basic Relationships Between Pixels. Definitions: f(x,y): digital image Pixels: q, p Subset of pixels of f(x,y): S. Neighbors of a Pixel. A pixel p at (x,y) has 2 horizontal and 2 vertical neighbors: (x+1,y), (x-1,y), (x,y+1), (x,y-1)

3.08k views • 20 slides

Raster conversion algorithms for line and circle

Raster conversion algorithms for line and circle. Introduction - Pixel addressing - Primitives and attributes Line drawing algorithms - DDA - Bresenham Circle generating algorithms - Direct method - Bresenham algorithm. Pixel addressing in raster graphics.

440 views • 19 slides

Derivatives: A First Look

Derivatives: A First Look. Average rate of change Instantaneous rate of change Derivative limit of difference quotients Differentiable implies continuity Derivative notation. Different rates of change. y=f(x)

469 views • 16 slides

The gradient as a normal vector

The gradient as a normal vector. Consider z=f(x,y) and let F(x,y,z) = f(x,y)-z. Let P=(x 0 ,y 0 ,z 0 ) be a point on the surface of F(x,y,z). Let C be any curve on the surface that passes through P and has the vector equation r (t) = <x(t),y(t),z(t)>. P. C.

257 views • 8 slides