JOURNAL ARTICLE

A spatiotemporal tensor-based multi-object matching algorithm

Abstract

A multi-object matching algorithm based on spatiotemporal tensor is proposed for stereo localization systems with binocular views. Multi-object matching is formulated as a graph matching problem, which forms an efficient and extensible framework for the various matching cases. Then, the spatiotemporal tensor, including appearance, geometric and temporal cues, is used to improve the reliability and accuracy rate of matching in various conditions. Also, a high-order graph matching algorithm is introduced and improved. The experimental evaluation shows that proposed algorithm is robust to various cases, accurate in terms of matching rate, while being time-consuming little.

Keywords:
Matching (statistics) Computer science Artificial intelligence 3-dimensional matching Blossom algorithm Object (grammar) Tensor (intrinsic definition) Algorithm Pattern recognition (psychology) Graph Optimal matching Computer vision Mathematics Theoretical computer science

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1
Cited By
0.32
FWCI (Field Weighted Citation Impact)
12
Refs
0.59
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Citation History

Topics

Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Neural Network Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Graph Theory and Algorithms
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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