Zoom Tracking And Its Applications
.
Zoom tracking and its applications.
Mach. Vis. Appl., 13(1):25-37, 2001
Online Version
A pdf version is available for download.
Abstract
We present a new active vision technique called zoom tracking. Zoom tracking is the continuous adjustment of a camera's focal length in order to keep a constant-sized image of an object moving along the camera's optical axis. Two methods for performing zoom tracking are presented: a closed-loop visual feedback algorithm based on optical flow, and use of depth information obtained from an autofocus camera's range sensor. We explore two uses of zoom tracking: recovery of depth information and improving the performance of scale-variant algorithms. We show that the image stability provided by zoom tracking improves the performance of algorithms that are scale variant, such as correlation-based trackers. While zoom tracking cannot totally compensate for an object's motion, due to the effect of perspective distortion, an analysis of this distortion provides a quantitative estimate of the performance of zoom tracking. Zoom tracking can be used to reconstruct a depth map of the tracked object. We show that under normal circumstances this reconstruction is much more accurate than depth from zooming, and works over a greater range than depth from axial motion while providing, in the worst case, only slightly less accurate results. Finally, we show how zoom tracking can also be used in time-to-contact calculations.
Keywords
- Focusing,
- Cameras,
- Algorithms,
- Optical Flows,
- Image Sensors,
- Correlation Methods,
- Object Recognition,
- Image Reconstruction,
- Calculations.
Co-authors
Bibtex Entry
@article{FaymanSRR01a,
title = {Zoom tracking and its applications.},
author = {Jeffrey A. Fayman and Oded Sudarsky and Ehud Rivlin and Michael Rudzsky},
year = {2001},
journal = {Mach. Vis. Appl.},
volume = {13},
number = {1},
pages = {25-37},
keywords = {Focusing; Cameras; Algorithms; Optical flows; Image sensors; Correlation methods; Object recognition; Image reconstruction; Calculations},
abstract = {We present a new active vision technique called zoom tracking. Zoom tracking is the continuous adjustment of a camera's focal length in order to keep a constant-sized image of an object moving along the camera's optical axis. Two methods for performing zoom tracking are presented: a closed-loop visual feedback algorithm based on optical flow, and use of depth information obtained from an autofocus camera's range sensor. We explore two uses of zoom tracking: recovery of depth information and improving the performance of scale-variant algorithms. We show that the image stability provided by zoom tracking improves the performance of algorithms that are scale variant, such as correlation-based trackers. While zoom tracking cannot totally compensate for an object's motion, due to the effect of perspective distortion, an analysis of this distortion provides a quantitative estimate of the performance of zoom tracking. Zoom tracking can be used to reconstruct a depth map of the tracked object. We show that under normal circumstances this reconstruction is much more accurate than depth from zooming, and works over a greater range than depth from axial motion while providing, in the worst case, only slightly less accurate results. Finally, we show how zoom tracking can also be used in time-to-contact calculations.}
}