Determining Angular Frequency from Video with a Generalized Fast Fourier Transform

Abstract

Suppose we are given a video of a rotating object and suppose we want to determine the rate of rotation solely from the video itself and its known frame rate. In this thesis, we present a new mathematical operator called the Geometric Sum Transform (GST) that can help one determine the angular frequency of the object in question. The GST is a generalization of the discrete Fourier transform (DFT) and as such, the two transforms have much in common. However, whereas the DFT is applied to a sequence of scalars, the GST can be applied to a sequence of vectors. Most importantly, we show that the GST, like the DFT, can (1) be used to estimate frequency and (2) can be computed surprisingly quickly. Indeed, we provide a Fast Geometric Sum Transform (FGST) algorithm that computes the GST in O(N logN) matrix-vector multiplications, where N is the number of images in the video sequence. This is a vast improvement over the O(N2) such multiplications required for a direct computation of the GST. The remainder of this thesis is devoted to proving other properties of the GST and giving proof-of-concept numerical examples.

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Document Details

Document Type
Technical Report
Publication Date
Mar 22, 2012
Accession Number
ADA557236

Entities

People

  • Lindsay N. Smith

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Cameras
  • Computational Complexity
  • Computations
  • Department Of Defense
  • Engineering
  • Fast Fourier Transforms
  • Frequency
  • Hilbert Space
  • Literature Surveys
  • Mathematics
  • Rotation
  • Sequences
  • Standards
  • United States
  • United States Government

Readers

  • Approximation Theory.
  • Graph Algorithms and Convex Optimization.
  • Information Retrieval