skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


  • Home
  • Search Results
  • Page 1 of 1

Search for: All records

Creators/Authors contains: "Liang, Kevin"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. ; ; ; ; ; ; ; ; (, IEEE International Conference on Intelligent Robots and Systems)
    To address the challenge of short-term object pose tracking in dynamic environments with monocular RGB input, we introduce a large-scale synthetic dataset Omni-Pose6D, crafted to mirror the diversity of real-world conditions. We additionally present a benchmarking framework for a comprehensive comparison of pose tracking algorithms. We propose a pipeline featuring an uncertainty-aware keypoint refinement network, employing probabilistic modeling to refine pose estimation. Comparative evaluations demonstrate that our approach achieves performance superior to existing baselines on real datasets, underscoring the effectiveness of our synthetic dataset and refinement technique in enhancing tracking precision in dynamic contexts. Our contributions set a new precedent for the development and assessment of object pose tracking methodologies in complex scenes. 
    more » « less
    Free, publicly-accessible full text available October 25, 2026
  2. ; ; ; ; ; ; ; (, Optics Letters)
    Supergrowth occurs when the local amplitude growth rate of a wave is greater than that predicted by the band limit. While generating supergrowth on demand requires precise source modulation, we demonstrate that supergrowth occurs naturally in a sum of random plane waves. We measure the supergrowing fractional area of transverse, monochromatic, fully developed speckle patterns. For speckle with a disk spectrum, we find that the average fractional supergrowing area approaches 20%. We compare the supergrowing and superoscillating fractional areas and find great similarity in behavior. Our results inform on the ubiquity of superphenomena in speckle patterns and are relevant to imaging and estimation. 
    more » « less
    Free, publicly-accessible full text available January 1, 2026
  3. ; ; (, Physical Review B)
    Full Text Available 
  4. ; (, Optics Express)
  5. ; ; (, Optics Express)
  6. ; ; (, Optics Express)
  7. ; ; ; (, Applied Optics)
  8. ; ; ; ; (, Computational Optics II)
    We present the definition of a new quantity, the pupil difference probability density (PDPD), and describe its use in the study of imaging systems. Formally, the PDPD is defined as the probability density that two random points over the pupil, with given separation, have a given wavefront error difference. Under this definition, the PDPD is the one-dimensional Fourier transform, of the error difference variable, of the OTF. Using the PDPD, we show that it is possible to understand how certain sources of error affect the OTF. Further, given its geometric interpretation, this formalism is useful for finding accurate analytic approximations to the OTF. 
    more » « less
    Full Text Available