Saturday, October 1, 2011

Reaction: A Survey of Algorithms for Volume Visualization

The author starts off by defining volume visualization and then introduces the reader to the background essential for visualizing volume. The datasets and the characteristics of volume like the cells, voxels, grids and lattices are explained.Two main categories of volume visualizing algorithms, DVR and SF and the different algorithms in these categories like Splatting, Ray casting,Marching cubes etc have been documented.

There were several concepts such as the depth fog attenuation, depth brightness attenuation in 'Viewing and Shading' section which I did not understand but overall the paper was definitely helpful in understanding the methods, complexities and challenges involved in volume visualization. The paper also gave a succinct description of the marching cubes algorithm.

Jobs: Triangle firm a finalist in Dell-sponsored contest

Good idea, for company and for you. 

Triangle firm a finalist in Dell-sponsored contest

Reaction: A Survey of Algorithms for Volume Visualization

Elvins gives a better overview of the principles that "Marching cubes" exemplifies. The article mentions the importance of animation in the process of generating these visualizations; an element I lost sight of while reading the "Marching Cubes" article. Animation is a powerful tool in the world of visualization. Coupling it with 3D renderings adds extensive functionality for several applications that require realistic renderings to reduce costs and increase safety.

I found the splatting algorithm presented in this article to be the most interesting. Elvins gives a different perspective on methods of rendering with this section where speed is favored over quality. The way he described the process in running the splatting algorithm helped to mentally visualize how a rendering would be generated. With improvements in hardware the rendering can occur so quickly it may not be as easy to visualize, as seen in this video:

Reaction: Imaging Vector Fields Using Line Integral Convolution

Cabral and Leedom give an insight into the work that is required to perform some common forms of image processing. Overall, I enjoyed reading this article because of the application of the algorithms on photo manipulation. As a Photoshop user, the DDA circular and turbulent convolution of image is something I take for granted since they are easy to impose on an image with a click of a button. Unfortunately, these techniques are not part of my usual photo post-processing tool-set since I do not see their purpose past making cool textures. The LIC algorithm, on the other hand, is something that I could see myself using in post-processing as action photography can sometimes be difficult to pull off.

Cabral and Leedom comment that 'spot noise [can] inaccurately represent the vector field' in some situations. In my opinion, to which extent can these inaccuracies be detected by the naked eye? Do the inaccuracies significantly affect the overall visualization?

Friday, September 30, 2011

Viz:Visualizaing The Fortune 500 since 1955

This is a visualization depicting the ranks of the fortune 500 companies since 1955. They can be sorted on revenue and profits. This is a simple visualization that represents a large set of data in a single graph.
The graph can be found here:

Reaction: Marching cubes: A high resolution 3D surface construction algorithm

I found it very interesting that 3D modeling was a possibility before I was born! The different examples of triangulated cubes provided in the article made it seem as if the complex calculations required for processing the marching cubes algorithm would produce a low-resolution model. Needless to say, the example renders near the end of the article blew me away.

Lorensen and Cline's decision to present their algorithm with respect to the medical field gave a unique perspective that made it easier to understand the utility of their research. The images of the algorithm in action are a good contrast to the immense benefits of 3D imagery versus 2D. The fact that these calculations were able to be computed on the hardware available when the research was performed makes it clear that 3D rendering will only get more refined and easier to produce as time goes on.

Reaction: Over Two Decades of Integration-Based, Geometric Flow Visualization

Geometric Flow Visualizations provide a change of pace in the types of visualizations we have seen in this class. The properties discussed in this article to describe characteristics flow visualizations may present were somewhat difficult to grasp as I was reading. I found that most of the properties mentioned would be helpful in presenting change in direction or movement when constructing this type of visualization.

The applications for these types of visualizations seem simple but effective. Although the visual examples presented in the article do not have visible numerical data, they provide a measurable guide for the viewer to grasp an overall change. This ability is something I would personally have trouble grasping if only a dataset were given to me.

Thursday, September 29, 2011

Find: How guys and girls see color

Something we discussed in class about the colors seen by a male and a female...

courtesy :

Lecture: Spatial Visualizations


Below please find the readings for my lecture next Wednesday. Achyuth Bukkapattanam will lead discussion. Please read all four (they are short):


Tuesday, September 27, 2011

Viz: Android powered 56 percent of smartphones sold in the last three months

Android a majority last qtr, blackberry in freefall. 

A funny looking bar chart that appears to be a treemap. 

Android powered 56 percent of smartphones sold in the last three months

Nielsen survey