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Recognizing 3D Object Using Photometric Invariant
(1995-04-22)
In this paper we describe a new efficient algorithm for recognizing 3D objects by combining photometric and geometric invariants. Some photometric properties are derived, that are invariant to the changes of illumination ...
Towards Intelligent Structures: Active Control of Buckling
(1994-05-01)
The buckling of compressively-loaded members is one of the most important factors limiting the overall strength and stability of a structure. I have developed novel techniques for using active control to wiggle a ...
An Analog VLSI Chip for Estimating the Focus of Expansion
(1996-08-21)
For applications involving the control of moving vehicles, the recovery of relative motion between a camera and its environment is of high utility. This thesis describes the design and testing of a real-time analog ...
Pose-Invariant Face Recognition Using Real and Virtual Views
(1996-03-28)
The problem of automatic face recognition is to visually identify a person in an input image. This task is performed by matching the input face against the faces of known people in a database of faces. Most existing ...
SketchIT: A Sketch Interpretation Tool for Conceptual Mechanical Design
(1996-03-13)
We describe a program called SketchIT capable of producing multiple families of designs from a single sketch. The program is given a rough sketch (drawn using line segments for part faces and icons for springs and ...
The Role of Fixation and Visual Attention in Object Recognition
(1995-07-21)
This research project is a study of the role of fixation and visual attention in object recognition. In this project, we build an active vision system which can recognize a target object in a cluttered scene efficiently ...
A Trainable System for Object Detection in Images and Video Sequences
(2000-05-01)
This thesis presents a general, trainable system for object detection in static images and video sequences. The core system finds a certain class of objects in static images of completely unconstrained, cluttered scenes ...
Support Vector Machines: Training and Applications
(1997-03-01)
The Support Vector Machine (SVM) is a new and very promising classification technique developed by Vapnik and his group at AT&T Bell Labs. This new learning algorithm can be seen as an alternative training technique ...
Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers
(1996-12-01)
The Support Vector (SV) machine is a novel type of learning machine, based on statistical learning theory, which contains polynomial classifiers, neural networks, and radial basis function (RBF) networks as special ...
Probabilistic Independence Networks for Hidden Markov Probability Models
(1996-03-13)
Graphical techniques for modeling the dependencies of randomvariables have been explored in a variety of different areas includingstatistics, statistical physics, artificial intelligence, speech recognition, image ...