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Proceedings International Workshop on Mobile Mapping Technology

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fullscreen: Proceedings International Workshop on Mobile Mapping Technology

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

Proceedings International Workshop on Mobile Mapping Technology
Cover
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Title page
Title page
Proceedings of International Workshop on Mobile Mapping Technology April 21-23, 1999, Maruay Garden Hotel, Bangkok, Thailand
Greeting from Bangkok.
PREFACE.
On behalf of the International Association of Geodesy (IAG) Working Group [...]
TECHNICAL PROGRAM.
[Session 1: Mobile Mapping (1)]
A ROBUST METHOD FOR REGISTERING 2.5D LASER RANGE IMAGES OF URBAN OBJECTS. Huijing ZHAO, Ryosuke SHIBASAKI.
AN INTELLIGENT MOBILE MAPPING SYSTEM. Naser El-Sheimy, Mike Chapman, and C. Tao.
A Mobile Mapping System Based on GPS, GIS and Multi-sensor. Deren Li.
AIRPORT DATA BASIS FOR TAGSY GUIDANCE SYSTEMS. W. Möhlenbrink, R. Bettermann.
INTEGRATING TECHNOLOGIES: DGPS, DEAD RECKONING AND MAP MATCHING. T. A. Hailes.
[Session 2: Mobile Mapping (2)]
FILTERALGORITHMS FOR OPTIMAL DETERMINATION OF POSITION AND ATTITUDE OF THE MOBILE MAPPING SYSTEM KISS. H. Sternberg, W. Caspary and H. Heister.
DEVELOPMENT OF AN INTEGRATED SYSTEM FOR MAPPING ROAD WIDTH USING DIGITAL VIDEO AND GLOBAL POSITIONING SYSTEM. Shanmugam Ganeshkumar, Kiyoshi HONDA, Shunji MURAI.
DIRECT PLATFORM ORIENTATION IN AERIAL AND LAND-BASED MAPPING PRACTICE. Dorota A. Grejner-Brzezinska, Charles K. Toth and Edward Oshel.
TOWARDS AUTOMATED PROCESSING OF MOBILE MAPPING IMAGE SEQUENCES. C. Tao, M. A. Chapman, and N. El-Sheimy, B. Chaplin.
[Poster Session (1) on Airborne & Spaceborne Remote Sensing (JARS)]
Generation of Digital Elevation Model derived from JERS1 SAR Interferometry. Mitsuharu TOKUNAGA.
GENERALIZATION TECHNIQUES FOR LAYERED NEURAL NETWORKS IN THE CLASSIFICATION OF REMOTELY SENSED IMAGES. Eihan SHIMIZU and Morito TSUTSUMI, Le Van TRUNG.
THE CRANES' NESTING ANALYSIS USING GIS - LANDSCAPE ECOLOGICAL APPLICATIONS -. Koichi HIRATA, Hiroshi MURAKAMI.
INTERPRETABILITY OF GEOGRAPHIC INFORMATION FROM HIGH RESOLUTION SATELLITE IMAGES. Toshiaki Hashimoto.
Reassessment of Todaro's Migration Model to Incorporate Socioeconomic and Natural Resource Environment by Using Remote Sensing and GIS: A Case of Thailand. Bhuwneshwar Prasad SAH, Eihan SHIMIZU and Morito TSUTSUMI.
LAND COVER OF ASIA. Ryutaro Tateishi.
Development of Drain Direction Model based onGTOPO30 and Global Data Sets. Shiro Ochi and Ryosuke Shibasaki.
[Session 3: Kinematic Real-time Positioning]
Positioning Principles and Accuracy of Airborne Laser- Ranging & Multispectral-lmaging Mapping System. Liu Shaochuang, You Hongjian, Xiang Maosheng, Liu Tong, Li Shukai.
Accuracy Assessment and Improvement for Level Survey using Real Time Kinematic (RTK) GPS. Dinesh Manandhar, Kiyoshi Honda, Shunji Murai, Sachio Kubo, Masahiro Yonemura.
Airborne Mapping System with GPS-supported Aerotriangulation. Deren Li, Xiuxiao Yuan.
[Session 4: Sensor Integration and Calibration]
The Calibration of Imaging Sensors Integrated into a Rapid Route Mapping System. C. S. Fraser, A. M. Judd.
CALIBRATING A ZOOM LENS CCD CAMERA FOR A TERRESTRIAL IMAGE BASED SURVEY SYSTEM. Y. D. Huang and D. Chen.
METHOD FOR ACCURATE CAMERA ORIENTATION FOR AUTOMOBILE PHOTOGRAMMETRIC SYSTEM. V. A. Knyaz, S. Yu. Zheltov.
MULTI-SENSOR MAP MATCHING CONCEPTS FOR POSITIONING OF ROAD AND RAIL VEHICLES. R. Czommer, W. Möhlenbrink.
SENSOR INTEGRATION AND CALIBRATION OF DIGITAL AIRBORNE THREE-LINE CAMERA SYSTEMS. Michael Cramer, Dirk Stallmann and Norbert Haala.
[Session 5A: Applications (1)]
Application of Photogrammetric Image Data for Roadway Construction. Guangping He.
SURVEYING AND MAPPING OF URBAN STREETS BY PHOTOGRAMMETRIC TRAVERSE. A. R. SILVA, J. C. BATISTA, R. A. OLIVEIRA, P. O. CAMARGO and J. F. C. SILVA.
[Session 5B: Real-time Imaging (ARIDA)]
ESTIMATION OF ACCURACY OF AIRBORNE LASER PROFILING. Koukichi Kimura, Teruvoshi Fujiwara, Yukihide Akiyama.
CRACK SITUATION GRASP OF DIGITAL IMAGE METHOD. Tatuhide NAKANE, Hisasi TAKAGI, Masaharu OZAWA.
Mobile Mapping Technologies for Safety Driving Assistance in ITS. Yutaka Shimogaki, Tooru Kitagawa, Yoshiki Yamano, Katunori Takahashi.
[Session 6A: Applications (2)]
Virtual Reality Model Created from Mobile Mapping Data as Interface to GIS. Krzysztof Gajdamowicz.
IMPROVED DEM EXTRACTION TECHNIQUES - COMBINING LIDAR DATA WITH DIRECT DIGITAL GPS/INS ORIENTED IMAGERY. Charles K. Toth and Dorota A. Grejner-Brzezinska.
Focal Plane Image Assembly of Subpixel. Si-Dong Zhong, Tian chan Mei.
[Session 6B: Real-time Imaging (ARIDA)]
A Tracking System for Construction vehicles with DGPS and RTK-GPS. Shun'ichi OHTSU, Tomonori TAKADA, Tatsunori SADA.
A METHOD OF ROAD REPRESENTATION IN 3D MAPPING TECHNOLOGY. Tsukasa Hosomura.
Fundamental Study on Ground-Based Sensor Integration for Spatial Data Acquisition. Mitsunori YOSHIMURA, Tetsuji ANAI, Hirofumi CHIKATSU, Ryosuke SHIBASAKI.
Fundamental Study on Development and Application of the Local Positioning System using Accelerometer and Gyroscope. Toshio KOIZUMI, Yasuyuki SHIRAI, Atsuro TAKEMOTO.
[Poster Session (2) on Imaging Sensing (ARIDA)]
THE METHOD OF Field INVESTIGATIONS USING DIGITAL IMAGE. Toshiaki Taguchi, Kosuke Tsuru, Hirofumi Chikatsu.
PERFORMANCE OF ARTIFICIAL RETINA CAMERA AND ITS APPLICATION. Yoichi KUNII, Hirofumi CHIKATSU.
MOTION ANALYSIS ON THE CONSTRUCTION PLANT USING SEQUENTIAL IMAGES. Sosuke YOSHIDA, Hirofumi CHIKATSU.
AUTO-TRACKING AND 3D MEASUREMENT FOR MOVING OBJECT USING VIDEO THEODOLITE. Tsutomu KAKIUCHI, Hirofumi CHIKATSU.
Generation of 3D View Map Using by Raster Base Data Processing. Kunihiko Ono, Shunji Murai, Vivarad Phonekeo and Shigetaka Yasue.
REMAPPING OF HISTORICAL MAPS USING MATHEMATICAL MORPHOLOGY AND ITS APPLICATION. Nobuhiro YAMADA, Hirofumi CHIKATSU.
A Comparative Study on Techniques for Optical Flow Estimation : On the Application to Vehicle Motion Analysis. Takashi FUSE and Eihan SHIMIZU.
Dynamic Analysis of Human Motion using Digital Video Camera mounted on Video Theodolite. Tetsuji ANAI, Hirofumi CHIKATSU.
A New Measurement System of Settlement At Airports Using GPS and Laser Level. Bunji Shigematsu.
[Session 7A: Automatic Object Extraction and Recognition]
INTEGRATION OF FEATURE AND SIGNAL MATCHING FOR OBJECT SURFACE EXTRACTION. Pakom Apaphant, James Bethel.
FEATURE EXTRACTION FROM MOBILE MAPPING IMAGERY SEQUENCES USING GEOMETRIC CONSTRAINTS. Fei Ma and Ron Li.
A MULTILAYER HOPFIELD NEURAL NETWORK FOR 3-D OBJECT RECOGNITION. Zhuowen Tu and Ron Li.
DATABASE GUIDED VERIFICATION AND UPDATING OF TRANSPORTATION OBJECTS WITH VERTICAL LINE FEATURES FROM MOBILE MAPPING IMAGE SEQUENCES. C. Tao.
Traffic Sign Detection from Image Sequences. W. B. Tong, J. Y. Hervé, P. Cohen.
ROBUSTNESS TEST TO OBJECT POSITIONING IN PROJECTIVE SPACE. Xingwen Wang, Deren Li.
[Session 7B: Mobile Mapping for Spatial Data Acquisition]
AUTOMATIC MEASUREMENT OF ROAD WIDTHS IN COLOUR STEREO SEQUENCES ACQUIRED BY A MOBILE MAPPING SYSTEM. Krzysztof Gajdamowicz.
Wearable Computing, Wireless Communication & Knowledge Discovery for Mobile Data Acquisition & Analysis. Klaus Brinkkötter-Runde and Ubbo Visser.
Development of a Low-Cost DGPS/DR System for Vehicle Tracking. Xiufeng He, Thor I. Fossen and Yongqi Chen.
OFF Method and Its Practice on Airborne GPS Data Processing for Photogrammetry. Chen Xiaoming, Liu Jiyu, Li Deren.
List of Registered Participants
Cover

Full text

3.2 Formation of Vertical Line Segments 
3.2.1 Vertical Line Grouping 
Line grouping is a complicated process since no prior knowledge is 
available to link isolated edges. In our case, a new grouping 
algorithm is designed based on the vertical line constraint. The main 
concern for grouping is how to achieve a trade-off on gap bridging. 
A strong linking process may produce many false line segments, 
while a weak linking process may lose many important line 
segments. 
It is observed that a vertical object of interest, such as a pole, has two 
vertical boundary lines. As shown in Figure 4, an ideal edge model 
of a vertical object, the edges located along the two boundary lines of 
the same object should have opposite edge directions and be within a 
certain distance. This presents a strong constraint for extraction of 
reliable vertical line features. Based upon the above analysis, the line 
grouping algorithm is composed of two phases: (1) grouping of 
primary line segments (to group the distinct line segments), and (2) 
grouping of secondary line segments (if the detected primary line is 
located on one side of the object boundary lines, the line segments 
parallel to this primary line are to be grouped). 
Phase 1: Grouping of primary line segments 
(1 .a) Scan the edge image from the left-top to the right-bottom, and 
find an unprocessed edge; 
(l.b) Take this edge point as a starting edge point, and construct a 
vertical “bridge” downwards, with a width of 3 pixels (shown 
in Figure 5). The length of the bridge is defined by the 
parameter “length of bridging gap”. In the first phase, only the 
distinct line segments are to be grouped, so that the length of 
bridging gap of 15 pixels is chosen. 
(l.c) If an edge is located in this bridge and its direction is the 
“same” (tolerance is ±15°) as that of the starting edge, this 
edge is recorded as a “compatible edge”, otherwise as an 
“incompatible edge”. 
Case 1: If the distance between a compatible and the starting 
point is less than half of the bridge length (8 pixels), link this 
edge to the starting point, take this edge as a new starting 
point, and go to (l.b). 
Case 2: If no compatible edge exists, but the number of 
compatible edges in this bridge is larger than the number of 
incompatible edges, link the closest compatible edge to the 
starting point, and take this edge as a new starting point. Go to 
(l.b). 
Case 3: If either of the two cases above is not found, go to step 
(l.a) and continue scanning. 
(l.d) Finally, if the length of the line segment composed of linked 
edges surpasses a threshold (50 pixels), the line segment is 
considered as a primary line segment and recorded into a line 
file. 
Phase 2: Grouping of secondary line segments 
The second phase focuses on the grouping of the line segments 
parallel to the primary line segments. This work is used to determine 
the conformance degree of the detected primary line segments. If 
parallel line segments are found, it is assumed that the primary line 
segment is likely located on the boundaries of a vertical object. 
According to the model of Figure 4, an associated line segment 
should have an opposite direction and be within a certain distance to 
the primary line segment. The grouping scheme is similar to the first 
phase except that the length of bridging gap is chosen differently. 
(2.a) Scan the surrounding area of a detected primary line segment 
within a range of ± 10 pixels, and find an edge whose 
direction is opposite to the direction of the primary line 
segment. The average direction value of the compatible edges 
composing the line segment is defined as the line direction. 
A Vertical Object 
An edge model 
Gray A 1 
value T 3 T 
.y=3> 
Edge magnitude 
i À 
o 
= * 
Edge direction 
Length of 
bridging gap 
Figure 4. An ideal edge model of a vertical object Figure 5. Budging grouping model 
Table 1. Representation of line segments 
ID No. 
Xs, Ys, Xe, Ye 
Length 
Number of edges 
Direction 
Stereo 
Parallel 
No. 5 
78 
37 
3° 
True 
True 
No. 6 
52 
18 
186° 
False 
False 
7A-4-3

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