VideoBrush/sup TM/: experiences with consumer video mosaicing

Sawhney, Harpreet; Kumar, Raman; Gendel, G.; Bergen, James R.; Dixon, Douglas; Paragano, V.

doi:10.1109/acv.1998.732858

Cited by 34 publications

(24 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our method is similiar to the frame-to-mosaic scheme of [37]. It is admittedly inferior to simultaneous solution but has been more expedient in practice.…”

Section: Resolving Inconsistencymentioning

confidence: 96%

See 1 more Smart Citation

Mobile Robot Localization from Large-Scale Appearance Mosaics

Kelly

2000

The International Journal of Robotics Research

View full text Add to dashboard Cite

A new practical, high-performance mobile robot localization technique is described which is motivated by the fact that many man-made environments contain substantially flat, visually textured surfaces of persistent appearance. While the tracking of image regions is much studied in computer vision, appearance is still a largely unexploited localization resource in commercially relevant guidance applications. We show how prior appearance models can be used to enable highly repeatable mobile robot guidance that, unlike commercial alternatives, is both infrastructure-free and free-ranging. Very large scale mosaics are constructed and used to localize a mobile robot operating in the modeled environment. Straightforward techniques from vision-based localization and mosaicking are used to produce a field-relevant AGV guidance system based only on vision and odometry. The feasibility, design, implementation, and pre-commercial field qualification of such a guidance system are described.

show abstract

“…Our method is similiar to the frame-to-mosaic scheme of [37]. It is admittedly inferior to simultaneous solution but has been more expedient in practice.…”

Section: Resolving Inconsistencymentioning

confidence: 96%

“…Applications include station keeping [41], video coding [23], image stabilization [50], and visualization [42]. Only recently have near real-time [37] and globally consistent [36] mosaicking solutions emerged.…”

Section: Prior Mosaicking Workmentioning

confidence: 99%

Mobile Robot Localization from Large-Scale Appearance Mosaics

Kelly

2000

The International Journal of Robotics Research

View full text Add to dashboard Cite

show abstract

“…It has been used to obtain super-resolution [4], [43], capture wide FOV urban and indoor scenes [6], [20], [32], aid robot navigation [12], compress video [22], [26], and for virtual reality and 3D environmental information [29], [40], [44]. Its extension to generalized mosaics enabled the creation of high dynamic range (HDR) images [1], [36], [38] and multispectral images [36], [37].…”

Section: Introductionmentioning

confidence: 99%

Generalized mosaicing: polarization panorama

Schechner

Nayar

2005

IEEE Trans. Pattern Anal. Machine Intell.

View full text Add to dashboard Cite

Abstract-We present an approach to image the polarization state of object points in a wide field of view, while enhancing the radiometric dynamic range of imaging systems by generalizing image mosaicing. The approach is biologicallyinspired, as it emulates spatially varying polarization sensitivity of some animals. In our method, a spatially varying polarization and attenuation filter is rigidly attached to a camera. As the system moves, it senses each scene point multiple times, each time filtering it through a different filter polarizing angle, polarizance, and transmittance. Polarization is an additional dimension of the generalized mosaicing paradigm, which has recently yielded high dynamic range images and multispectral images in a wide field of view using other kinds of filters. The image acquisition is as easy as in traditional image mosaics. The computational algorithm can easily handle nonideal polarization filters (partial polarizers), variable exposures, and saturation in a single framework. The resulting mosaic represents the polarization state at each scene point. Using data acquired by this method, we demonstrate attenuation and enhancement of specular reflections and semireflection separation in an image mosaic.

show abstract

“…More recent efforts have focused on imposing the available non-temporal spatial constraints to produce a globally consistent mosaic [21,126,137,138]. These methods formulate the problem as the optimization of a global cost function parameterized by all of the image to mosaic frame homography parameters.…”

Section: Global Mosaickingmentioning

confidence: 99%

Large-area visually augmented navigation for autonomous underwater vehicles

Eustice¹

2005

View full text Add to dashboard Cite

This thesis describes a vision-based, large-area, simultaneous localization and mapping (SLAM) algorithm that respects the low-overlap imagery constraints typical of autonomous underwater vehicles (AUVs) while exploiting the inertial sensor information that is routinely available on such platforms. We adopt a systems-level approach exploiting the complementary aspects of inertial sensing and visual perception from a calibrated pose-instrumented platform. This systems-level strategy yields a robust solution to underwater imaging that overcomes many of the unique challenges of a marine environment (e.g., unstructured terrain, low-overlap imagery, moving light source).Our large-area SLAM algorithm recursively incorporates relative-pose constraints using a view-based representation that exploits exact sparsity in the Gaussian canonical form. This sparsity allows for efficient O(n) update complexity in the number of images composing the view-based map by utilizing recent multilevel relaxation techniques. We show that our algorithmic formulation is inherently sparse unlike other feature-based canonical SLAM algorithms, which impose sparseness via pruning approximations. In particular, we investigate the sparsification methodology employed by sparse extended information filters (SEIFs) and offer new insight as to why, and how, its approximation can lead to inconsistencies in the estimated state errors. Lastly, we present a novel algorithm for efficiently extracting consistent marginal covariances useful for data association from the information matrix.In summary, this thesis advances the current state-of-the-art in underwater visual navigation by demonstrating end-to-end automatic processing of the largest visually navigated dataset to date using data collected from a survey of the RMS Titanic (path length over 3 km and 3100 m 2 of mapped area). This accomplishment embodies the summed contributions of this thesis to several current SLAM research issues including scalability, 6 degree of freedom motion, unstructured environments, and visual perception.

show abstract

VideoBrush/sup TM/: experiences with consumer video mosaicing

Cited by 34 publications

References 17 publications

Mobile Robot Localization from Large-Scale Appearance Mosaics

Mobile Robot Localization from Large-Scale Appearance Mosaics

Generalized mosaicing: polarization panorama

Large-area visually augmented navigation for autonomous underwater vehicles

Contact Info

Product

Resources

About