Learning-based spatio-temporal vehicle tracking and indexing for transportation multimedia database systems

Journal article

Peer reviewed

Shu-Ching CHEN, Mei-Ling SHYU, Srinivas PEETA and CHENGCUI CHENGCUI ZHANG

IEEE transactions on intelligent transportation systems, Vol.4(3), pp.154-167

2003

Abstract

Pattern recognition. Digital image processing. Computational geometry

Memory organisation. Data processing

Information systems. Data bases

Exact sciences and technology

Applied sciences

Software

Artificial intelligence

Road transportation and traffic

Ground, air and sea transportation, marine construction

Computer science; control theory; systems

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Collaboration types: Domestic collaboration
Citation topics: 4 Electrical Engineering, Electronics & Computer Science; 4.17 Computer Vision & Graphics; 4.17.953 Object Tracking
Web Of Science research areas: Engineering, Civil; Engineering, Electrical & Electronic; Transportation Science & Technology
ESI research areas: Engineering

This output has contributed to the advancement of the following goals:

Source: InCites

Title: Learning-based spatio-temporal vehicle tracking and indexing for transportation multimedia database systems
Creators: Shu-Ching CHEN - Distributed Multimedia Information System Laboratory, School of Computer Science, Florida International University, Miami, FL 33199, United States
Mei-Ling SHYU - Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL 33124, United States
Srinivas PEETA - School of Civil Engineering, Purdue University, West Lafayette, IN 47907, United States
CHENGCUI CHENGCUI ZHANG - Distributed Multimedia Information System Laboratory, School of Computer Science, Florida International University, Miami, FL 33199, United States
Publication Details: IEEE transactions on intelligent transportation systems, Vol.4(3), pp.154-167
Publisher: Institute of Electrical and Electronics Engineers; Piscataway, NJ
Academic Unit: College of Engineering; CoE - Electrical & Computer Engineering
Language: English
Resource Type: Journal article
Record Identifier: 991031559848802976