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A method is introduced to track the object's motion and estimate its pose directly from 2-D image sequences. Scale-invariant feature transform (SIFT) is used to extract corresponding feature points from image sequences. We demonstrate that pose estimation from the corresponding feature points can be formed as a solution to Sylvester's equation. We show that(More)
Aggregate nearest neighbor query, which returns a common interesting point that minimizes the aggregate distance for a given query point set, is one of the most important operations in spatial databases and their application domains. This paper addresses the problem of finding the aggregate nearest neighbor for a merged set that consists of the given query(More)
Particle filters have been introduced as a powerful tool to estimate the posterior density of nonlinear systems. These filters are also capable of processing data online as required in many practical applications. In this paper, we propose a novel technique for video stabilization based on the particle filtering framework. Scale-invariant feature points are(More)
We describe Pantheia, a system that constructs virtual models of real spaces from collections of images, through the use of visual markers that guide and constrain model construction. To create a model users simply 'mark up' the real world scene by placing preprinted markers that describe scene elements or impose semantic constraints. Users then collect(More)
In this paper, we introduce a method to estimate the object's pose from multiple cameras. We focus on direct estimation of the 3D object pose from 2D image sequences. Scale-Invariant Feature Transform (SIFT) is used to extract corresponding feature points from adjacent images in the video sequence. We first demonstrate that centralized pose estimation from(More)
—There is a significant interest in the research community to develop large scale, high performance implementations of neuromorphic models. These have the potential to provide significantly stronger information processing capabilities than current computing algorithms. In this paper we present the implementation of five neuromorphic models on a 50 TeraFLOPS(More)
In many circumstances, including e-learning, there is a need to reorganize digital resources, scattered in many places, into a coherently accessible repository. This paper introduces a methodology to do the job efficiently. Specifically , the resources that the scheme needs to handle presents the following challenges, 1) mass, 2) various data types, 3)(More)
In this paper, we present a general framework for analysis of plenop-tic sampling by investigating the spectral analysis of plenoptic imaging. The proposed framework provides a unified representation that generalizes several existing methods for plenoptic sampling. The plenoptic sampling theory presented extends the study of plenop-tic imaging to parallel(More)