Proceedings International Workshop on Mobile Mapping Technology

li, rongxing

Bibliographic data

Monograph

Persistent identifier:: 856671290

Author:: Li, Rongxing

Title:: Proceedings International Workshop on Mobile Mapping Technology

Sub title:: April 21 - 23, 1999, Bangkok, Thailand

Scope:: 1 Online-Ressource (Getr. Zählung [ca. 400 Seiten])

Year of publication:: 1999

Place of publication:: London

Publisher of the original:: RICS Books

Identifier (digital):: 856671290

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: [Session 7A: Automatic Object Extraction and Recognition]

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: DATABASE GUIDED VERIFICATION AND UPDATING OF TRANSPORTATION OBJECTS WITH VERTICAL LINE FEATURES FROM MOBILE MAPPING IMAGE SEQUENCES. C. Tao.

Document type:: Monograph

Structure type:: Chapter

DATABASE GUIDED VERIFICATION AND UPDATING OF TRANSPORTATION OBJECTS WITH VERTICAL LINE FEATURES FROM MOBILE MAPPING IMAGE SEQUENCES C. Tao, Assistant Professor Dept, of Geomatics Engineering, The University of Calgary 2500 University Dr., NW, Calgary, Alberta, Canada, T2N 1N4 Tel: (403) 220-5826, Fax: (403) 284-1980, Email: ctao@uc;dgary.ca KEY WORDS: Mobile mapping, transportation GIS, line feature extraction, multiple image matching, dynamic image sequences analysis, and multinocular line reconstruction. ABSTRACT A new approach is developed for automated verification and updating of the transportation objects, such as traffic signs, street light poles, etc., in a transportation database using road image sequences collected by the mobile mapping system. The existing transportation databases are used to predict the positions of the desired objects. Since the image sequences have been georeferenced using a GPS/INS technique, the positions of these desired objects in the images can be determined. Multiple constraints available in the mobile imaging system are utilized, and multiple image based feature extraction, image matching and line reconstruction algorithms are designed to detect objects in images and then update an object database. The evaluation of the approach in terms of reliability and accuracy has been conducted using real image tests. The results demonstrate that the road image sequences can be employed to update transportation databases in an automatic and cost-effective manner 1. INTRODUCTION Recently, GIS-T (transportation) has gained a great attention in both GIS and transportation communities. The maintenance and updating of transportation infrastructure databases along road corridors has been a challenging issue to transportation departments. Are not only the accuracy but also the currency of data stored in these database critical to GIS-based planning, analysis and management. Preferably, these databases need to be updated on a yearly or bi-yearly basis. Figure 1. VISAT mobile mapping system Mobile mapping technology has been proven an efficient and cost- effective approach for collecting transportation related spatial data along road corridors. The van-based mobile mapping system integrating multiple sensors, GPS, INS and CCD cameras is able to offer high-quality and georeferenced digital image sequences of road scenes. The 3-D coordinated of any object of interest appearing in at least two images can be determined by means of a post-mission photogrammetric processing. At the University of Calgary, a significant amount of research has devoted towards development of multi-sensor integrated technology and employment of mobile mapping images for various GIS applications. This research work was conducted based on the VISAT mobile mapping system (Schwarz et al., 1993). In the current implementation, eight CCD cameras have been mounted on the top of a van so that the system is able to capture road images with a field of view of 180 degree (Figure 1). In most urban areas, transportation databases already existed. However, to update the databases is not only time-consuming but also labor-intensive, since field surveys are extensively involved. It is a fact that a survey crew has to be sent out to examine the conditions of infrastructure, mark out missing objects, and re-survey moved objects on a regular basis. In this paper, an innovative approach is proposed to automate the procedure of examining and updating transportation objects with linear features in a database using both mobile mapping image sequences and existing object databases. Most transportation objects have distinctive line features in images and these line features are approximately vertical with respect to the ground. This type of objects forms a large group in transportation infrastructure, such as, traffic signs, street light poles, power-line poles, and fire hydrants. Due to this reason, in the proposed approach, a line feature extraction algorithm along with a multinocular line matching algorithm are developed to detect and verify the objects from image sequences, and a multinocular line based photogrammetric reconstruction technique is then used to determine the 3-D coordinates of the objects. The literature regarding extraction of line features is very extensive (Chen and Huang, 1990; Engelbrecht and Wahl, 1988; Liu et al., 1990). The major advantage of the approach proposed in this paper is that multiple constraints are developed and utilized in the design and implementation of the approach. These constraints include (1) the prior information of object positions obtained from an existing database, (2) stereoscopic and sequential multiple image geometry of objects from georeferenced image sequences, and (3) vertical line features of objects in the images. 2. OVERVIEW OF THE APPROACH The systematic overview of the proposed approach is illustrated in Figure 2. It consists of three main modules:

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