Using inter-feature-line consistencies for sequence-based object recognition
Journal
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Journal Volume
3021
Pages
108-120
Date Issued
2004
Author(s)
Chen J.-H
Abstract
An image sequence-based framework for appearance-based object recognition is proposed in this paper. Compared with the methods of using a single view for object recognition, inter-frame consistencies can be exploited in a sequence-based method, so that a better recognition performance can be achieved. We use the nearest feature line method (NFL) [8] to model each object. The NFL method is extended in this paper by further integrating motion-continuity information between features lines in a probabilistic framework. The associated recognition task is formulated as maximizing an a posteriori probability measure. The recognition problem is then further transformed to a shortest-path searching problem, and a dynamic-programming technique is used to solve it. © Springer-Verlag 2004.
Other Subjects
Computer vision; Dynamic programming; Image processing; A-posteriori probabilities; Appearance-based object recognition; Dynamic programming techniques; Feature lines; Image sequence; Nearest feature line method; Probabilistic framework; Shortest path searching; Object recognition
Type
journal article