Feature guided pixel matching and segmentation in motion image sequences

The problem of feature correspondences and trajectory finding for a long image sequence has received considerable attention. In this research, a coarse-to-fine algorithm is developed to obtain pixel trajectories through the sequence and to segment them into subsets corresponding to objects moving distinctly. First, a coarse-scale point-feature detector is used to detect point features that are then used to form a 3D dot pattern in the spatio-temporal region. The trajectories are extracted as 3D curves formed by the points using perceptual grouping. The set of feature points in each frame is divided into subsets corresponding to objects moving with different motion, using a measure of motion similarity between feature points.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Charan, Ram

Contributors dc:contributor

• Ahuja, Narendra

• Engineering, Electronics and Electrical
• Artificial Intelligence
• Computer Science

Statement dc:rights

• Copyright 1995 Charan, Ram

Language dc:language

eng

Identifier

AAI9624308
(UMI)AAI9624308

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/21023