We present a technique for the computation of 2D component velocity from image sequences. Initially, the image sequence is represented by a family of spatiotemporal velocity-tuned linear filters. Component velocity, computed from spatiotemporal responses of identically tuned filters, is expressed in terms of the local first-order behavior of surfaces of constant phase. Justification for this definition is discussed from the perspectives of both 2D image translation and deviations from translation that are typical in perspective projections of 3D scenes. The resulting technique is predominantly linear, efficient, and suitable for parallel processing. Moreover, it is local in space-time, robust with respect to noise, and permits multiple estimates within a single neighborhood. Promising quantiative results are reported from experiments with realistic image sequences, including cases with sizeable perspective deformation.

Fourier transform and applications

Computation of component image velocity from local phase information

This book presents a comprehensive treatment of signals and linear systems at an introductory level. The text emphasizes the physical appreciation of concepts rather than mere mathematical manipulation of symbols. Mathematics is used to enhance physical and intuitive understanding rather than to prove axiomatic theory. Theoretical results are frequently supported by carefully chosen examples and analogies. The organization of the book permits a great deal of flexibility in teaching the continuous-time and discrete-time concepts. The natural sequence of chapters is meant to integrate continuous-time and discrete-time analysis. It is also possible to use a sequential approach in which all the continuous-time analysis is covered first, followed by discrete-time analysis. Therefore, the book can adapt either of the most common approaches to teach signals and systems course.

Linear systems and signals

The problem of reconstruction a function from spherical means is at the heart of several modern imaging modalities and other applications. In this paper we derive universal back-projection type reconstruction formulas for recovering a function in arbitrary dimension from averages over spheres centered on the boundary an arbitrarily shaped smooth convex domain. Provided that the unknown function is supported inside that domain, the derived formulas recover the unknown function up to an explicitly computed smoothing integral operator. For elliptical domains the integral operator is shown to vanish and hence we establish exact inversion formulas for recovering a function from spherical means centered on the boundary of elliptical domains in arbitrary dimension.

Universal inversion formulas for recovering a function from spherical means

A prototype field-deployable acoustic insect flight detector was constructed from a noise-canceling microphone coupled to an off-the-shelf digital sound recorder capable of 10 h recordings. The system was placed in an urban forest setting 25 times over the course of the summer of 2004, collecting 250 h of ambient sound recordings that were downloaded to a personal computer and used to develop detection routines. These detection routines operated on short segments of sound (0.093 s, corresponding to 4096 samples at 44100 Hz). A variety of approaches were implemented to detect insect flight tones. Simple approaches, involving sensing the fundamental frequency (1st harmonic) and 2nd harmonic, were capable of detecting insects, but generated large numbers of false positives because of other ambient sounds including human voices, birds, frogs, automobiles, aircraft, sirens, and trains. In contrast, combining information from the first four harmonics, from the interharmonic regions, and from the sound envelope, reduced false positives greatly. Specifically, in the 250 h of recordings, 726 clear insect buzzes were detected by the final algorithm, with only 52 false positives (6.5%). Running the final algorithm with all criteria liberalized by 20% increased the number of clear insect buzzes by 8%, to 784, but increased false positives to 471 (28% of total detections). The potential of using this approach for detecting mosquito activity using low-cost sensors is discussed.

methods

https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1055&context=abe_eng_pubs

Fourier transform and applications

Citations

Computation of component image velocity from local phase information

Linear systems and signals

Universal inversion formulas for recovering a function from spherical means

Detecting Insect Flight Sounds in the Field: Implications for Acoustical Counting of Mosquitoes

Measurement of temperature and temperature profile of an axisymmetric gaseous flames using Lau phase interferometer with linear gratings

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