Recognition of user-defined video object models using weighted graph homomorphisms

Dirk Farin; Peter H. N. de With; Wolfgang Effelsberg

doi:10.1117/12.476522

7 May 2003 Recognition of user-defined video object models using weighted graph homomorphisms

Dirk Farin, Peter H. N. de With, Wolfgang Effelsberg

Proceedings Volume 5022, Image and Video Communications and Processing 2003; (2003) https://doi.org/10.1117/12.476522
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

In this paper, we propose a new system for video object detection based on user-defined models. Object models are described by 'model graphs' in which nodes represent image regions and edges denote spatial proximity. Each node is attributed with color and shape information about the corresponding image region. Model graphs are specified manually based on a sample image of the object. Object recognition starts with automatic color segmentation of the input image. For each region, the same features are extracted as specified in the model graph. Recognition is based on finding a subgraph in the image graph that matches the model graph. Evidently, it is not possible to find an isomorph subgraph, since node and edge attributes will not match exactly. Furthermore, the automatic segmentation step leads to an oversegmented image. For this reason, we employ inexact graph matching, where several nodes of the image graph may be mapped onto a single node in the model graph. We have applied our object recognition algorithm to cartoon sequences. This class of sequences is difficult to handle with current automatic segmentation algorithms because the motion estimation has difficulties arising from large homogeneous regions and because the object appearance is typically highly variable. Experiments show that our algorithm can robustly detect the specified objects and also accurately find the object boundary.

Citation Download Citation

Dirk Farin, Peter H. N. de With, and Wolfgang Effelsberg "Recognition of user-defined video object models using weighted graph homomorphisms", Proc. SPIE 5022, Image and Video Communications and Processing 2003, (7 May 2003); https://doi.org/10.1117/12.476522

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available