Holistic Video Stitching for Street Panorama

Zhou, Zihan; Min, Kerui; Ma, Yi

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https://hdl.handle.net/2142/74361 Copy

Description

Title

Holistic Video Stitching for Street Panorama

Author(s)

• Zhou, Zihan
• Min, Kerui
• Ma, Yi

Issue Date

2012-04

Keyword(s)

• Panorama
• Street-view
• Low-rank matrix

Date of Ingest

• 2015-04-06T20:54:52Z
• 2017-07-14T23:14:42Z

Abstract

In this paper, we address how to automatically generate a panorama for a street view from a long video sequence. We model the panorama as a low-rank matrix and formulate the problem as one of robust recovery of the low-rank matrix from highly incomplete, corrupted, deformed measurements (the video frames). We leverage powerful high-dimensional convex optimization tools from compressive sensing of sparse signals and low-rank matrices to solve this problem. In particular, we show how the new method can effectively remove severe occlusions or corruptions (caused by trees, cars, or reflections, etc.), and obtain clean, intrinsic street panoramas that are consistent with all frames. We also show how our method can automatically and robustly establish pixel-wise accurate registration among all the video frames. We demonstrate the effectiveness of our method by conducting extensive experimental comparison with other popular video stitching methods such as AutoStitch and Adobe Photoshop.

Publisher

Coordinated Science Laboratory, University of Illinois at Urbana-Champaign

Series/Report Name or Number

Coordinated Science Laboratory Report no. UILU-ENG-12-2202, DC-255

Type of Resource

text

Genre of Resource

Report (Grant or Annual)

Language

English

Permalink

http://hdl.handle.net/2142/74361

Sponsor(s)/Grant Number(s)

National Science Foundation / NSF IIS 11-16012

Owning Collections