S. Lodha

Publications
Influence

A. Pang, C. Wittenbrink, S. Lodha
Computer Science
The Visual Computer
1 September 1996

We present our results in uncertainty visualization for environmental visualization, surface interpolation, global illumination with radiosity, flow visualization, and figure animation. Expand

Sonification Report: Status of the Field and Research Agenda Prepared for the National Science Foundation by members of the International Community for Auditory Display

Terri L. Bonebright, P. Cook, +15 authors Sever Tipei
Political Science
1999

The purpose of this paper is to provide an overview of sonification research, including the current status of the field and a proposed research agenda. This paper was prepared by an interdisciplinary… Expand

Supervised Parametric Classification of Aerial LiDAR Data

Amin P. Charaniya, R. Manduchi, S. Lodha
Mathematics, Computer Science
Conference on Computer Vision and Pattern…
27 June 2004

We classify 3D aerial LiDAR height data into roads, grass, buildings, and trees using a supervised parametric classification algorithm. Expand

Aerial Lidar Data Classification using AdaBoost

S. Lodha, D. Fitzpatrick, D. Helmbold
Computer Science
Sixth International Conference on 3-D Digital…
21 August 2007

We use the AdaBoost algorithm to classify 3D aerial lidar data into four categories: road, grass, buildings, and trees. Expand

Aerial LiDAR Data Classification Using Support Vector Machines (SVM)

S. Lodha, Edward J. Kreps, D. Helmbold, D. Fitzpatrick
Computer Science
Third International Symposium on 3D Data…
14 June 2006

We classify 3D aerial LiDAR scattered height data into buildings, trees, roads, and grass using the support vector machine (SVM) algorithm. Expand

Glyphs for Visualizing Uncertainty in Vector Fields

C. Wittenbrink, A. Pang, S. Lodha
Computer Science
IEEE Trans. Vis. Comput. Graph.
1 September 1996

We show enhanced visualizations, data together with their uncertainty information, that may improve understanding of environmental vector field data quality. Expand

A generic structure-from-motion framework

S. Ramalingam, S. Lodha, P. Sturm
Computer Science
Comput. Vis. Image Underst.
1 September 2006

We introduce a generic structure-from-motion approach based on a previously introduced, highly general imaging model, that allows to reconstruct scenes from calibrated images, possibly taken by cameras of different types (cross-camera scenarios). Expand

UFLOW: visualizing uncertainty in fluid flow

S. Lodha, A. Pang, R. Sheehan, C. Wittenbrink
Computer Science
Proceedings of Seventh Annual IEEE Visualization…
27 October 1996

This paper presents UFLOW-a system for visualizing uncertainty in fluid flow. Expand

Scattered Data Techniques for Surfaces

S. Lodha, R. Franke
Mathematics, Computer Science
Scientific Visualization Conference (dagstuhl '97…
9 June 1997

This survey presents several techniques for solving variants of the following scattered data interpolation problem: given a finite set of N points in R3, find a surface that interpolates the given set of points. Expand

Towards complete generic camera calibration

S. Ramalingam, P. Sturm, S. Lodha
Mathematics, Computer Science
IEEE Computer Society Conference on Computer…
20 June 2005

We consider the problem of calibrating a highly generic imaging model, that consists of a non-parametric association of a projection ray in 3D to every pixel in an image. Expand

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