دانلود رایگان مقاله فشرده سازی نسل TIN برای وسایل نقلیه مبتنی بر سیستم نقشه برداری سیار

عنوان فارسی
فشرده سازی نسل TIN و توده نقطه ای برای وسایل نقلیه مبتنی بر سیستم نقشه برداری سیار
عنوان انگلیسی
TIN generation and point-cloud compression for vehicle-based mobile mapping systems
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
10
سال انتشار
2015
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
کد محصول
E69
رشته های مرتبط با این مقاله
مهندسی فناوری اطلاعات و ارتباطات و مهندسی فناوری اطلاعات
گرایش های مرتبط با این مقاله
دیتا و امنیت شبکه و سامانه های شبکه ای
مجله
مهندسی انفورماتیک پیشرفته
دانشگاه
دانشگاه الکترو ارتباطات، ژاپن
کلمات کلیدی
سیستم نقشه برداری تلفن همراه، نقطه ابر، لیزر اسکن، مثلثی شبکه نامنظم، نسل مش، فشرده سازی هندسه
چکیده

Abstract


The vehicle-based mobile mapping system (MMS) is effective for capturing dense 3D data of roads, roadside objects and buildings. Since discrete points are not convenient for many application systems, a triangulated irregular network (TIN) is often generated from point-clouds. However, TIN data require two or three times larger storage than point-clouds. If TIN models can be promptly generated while loading point-clouds, it would not be necessary to store huge TIN models on a hard disk. In this paper, we propose two efficient TIN generation methods according to types of laser scanners. One is the line-by-line TIN generation method, and the other is the GPS-time based method. These methods can quickly generate TIN models based on scan lines of laser scanners. In addition, we introduce a new compression method to reduce the loading time of point-clouds. Our compression method is also based on the scan lines of laser scanners. Since points captured by a MMS tend to be positioned on nearly straight lines, their data size can be significantly reduced by coding the second order differences.

نتیجه گیری

7. Conclusions


In this paper, we introduced efficient TIN generation methods for point-clouds captured by MMSs. We proposed two methods according to types of laser scanners; namely, the line-by-line method, and the GPS-time based method. We also proposed adaptive triangulation to reduce thin triangles and improve efficiency. Our experimental results show that our methods can very quickly generate TIN models. We also introduced a compressed representation for point-clouds. Since points tend to be placed on nearly straight lines, their data size can be significantly reduced by coding second order differences. In our experiments, our method signifi- cantly reduced the data sizes of point-clouds. For future work, we would like to develop TIN generation for overlapping scan lines, because our methods generates distorted TIN models when the scan lines are overlapping. We would also like to investigate a trade-off between quality and performance in more detail and estimate adequate quality parameters.


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