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Evaluation of the effect of images' geometric resolution on the 3D model quality in automated close-range photogrammetry

تقييم تأثير دقة التمييز الهندسية للصور على نوعية النموذج ثلاثي الأبعاد في المساحة التصويرية القريبة المؤتمتة

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 Publication date 2018
  fields topography
and research's language is العربية
 Created by Shamra Editor




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The main objective of this research is to study the effect of the accuracy of images' geometric resolution only on the geometric quality of the resulted three-dimensional model. In this research, all factors that affect the quality of the model are fixed and the geometric resolution is changed only for the used images. The number of captured images, the number and the distribution and the accuracy of control points, the camera being used and whether or not it is calibrated, are among the most important factors influencing the modeling process. In order to neutralize the effect of the inner parameters of the used camera, a process of calibration was achieved. On the other hand, we have pre-planned the process of photography to avoid problems resulting from the lack or increase the number of images, that directly affect the quality and completeness of the model. In addition, accurate control data obtained from precise survey work (horizontal geodetic network and leveling network) was applied. In this study, we examined the effect of image resolution on the generation of a dense cloud of points by applying the Structure from Motion (SfM) and deducing the surface model and the orthophoto of a facade of a building at Tishreen University.


Artificial intelligence review:
Research summary
تهدف هذه الدراسة إلى تقييم تأثير دقة التمييز الهندسية للصور على نوعية النموذج ثلاثي الأبعاد الناتج في المساحة التصويرية القريبة المؤتمتة. تم تثبيت جميع العوامل المؤثرة الأخرى وتغيير دقة التمييز فقط للصور المستخدمة. تم استخدام طريقة البنية انطلاقاً من الحركة (SfM) لتوليد غمامة كثيفة من النقاط واستنتاج النموذج السطوحي والصورة المصححة عامودياً لواجهة من واجهات منشأ في جامعة تشرين. تم التقاط الصور باستخدام آلة تصوير مرفقة مع هاتف نقال بثلاث دقات تمييز مختلفة: مرتفعة، متوسطة، ومنخفضة. أظهرت النتائج أن دقة التمييز الهندسية للصور تؤثر بشكل مباشر على نوعية النموذج ثلاثي الأبعاد، حيث انخفضت الدقة الهندسية للنموذج بنسبة 31% تقريباً عند استخدام دقة تمييز منخفضة مقارنة بدقة التمييز العظمى. كما أن الدقة الهندسية للأورتوفوتو الناتج كانت أفضل بمرتين في حالة دقة التمييز العظمى مقارنة بدقة التمييز المتوسطة، وأفضل بأربع مرات مقارنة بدقة التمييز المنخفضة. أوصت الدراسة باستخدام صور ذات دقة تمييز بحدود 4 ميغابيكسل على الأقل للحصول على نماذج ثلاثية الأبعاد جيدة من الناحية الهندسية مع زمن معالجة متوسط، وأهمية التخطيط الجيد لعملية التصوير الأرضي.
Critical review
دراسة نقدية: تعتبر هذه الدراسة مهمة في مجال المساحة التصويرية القريبة المؤتمتة، حيث تسلط الضوء على تأثير دقة التمييز الهندسية للصور على نوعية النماذج ثلاثية الأبعاد. ومع ذلك، كان من الممكن أن تكون الدراسة أكثر شمولية إذا تم اختبار تأثير عوامل أخرى مثل الإضاءة والبيئة المحيطة على النتائج. كما أن استخدام هاتف نقال كآلة تصوير قد لا يعكس الدقة المطلوبة في التطبيقات الصناعية الدقيقة. كان من الأفضل استخدام كاميرات متخصصة للحصول على نتائج أكثر دقة وموثوقية. بالإضافة إلى ذلك، كان من الممكن توسيع نطاق الدراسة ليشمل تطبيقات أخرى غير الواجهات المعمارية لتحسين شمولية النتائج.
Questions related to the research
  1. ما هو الهدف الرئيسي من هذه الدراسة؟

    الهدف الرئيسي هو دراسة تأثير دقة التمييز الهندسية للصور على النوعية الهندسية للنموذج ثلاثي الأبعاد الناتج في المساحة التصويرية القريبة المؤتمتة.

  2. ما هي الطريقة المستخدمة لتوليد غمامة كثيفة من النقاط في هذه الدراسة؟

    تم استخدام طريقة البنية انطلاقاً من الحركة (SfM) لتوليد غمامة كثيفة من النقاط.

  3. ما هي دقات التمييز الهندسية الثلاث التي تم استخدامها في الدراسة؟

    تم استخدام ثلاث دقات تمييز هندسية: مرتفعة (8 ميغابيكسل)، متوسطة (ربع قيمة دقة التمييز المرتفعة)، ومنخفضة (ثمن قيمة دقة التمييز المرتفعة).

  4. ما هي التوصيات التي خلصت إليها الدراسة؟

    أوصت الدراسة باستخدام صور ذات دقة تمييز بحدود 4 ميغابيكسل على الأقل للحصول على نماذج ثلاثية الأبعاد جيدة من الناحية الهندسية مع زمن معالجة متوسط، وأهمية التخطيط الجيد لعملية التصوير الأرضي.


References used
Remondino، F.، Spera، M.G.، Nocerino، E.، Menna، F.، Nex، F.، 2014. State of the art in high density image matching. In: The Photogrammetric Record 29، pp. 144–166. doi:10.1111/phor.12063
Förstner, W., 1986. A feature-based correspondence algorithm for image matching. International Archives of Photogrammetry and Remote Sensing 26, 150–166
Nocerino, E., Menna, F., Remondino F., 2014. Accuracy of typical photogrammetric networks in cultural heritage 3D modelling projects. The Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., Volume XL-5, 465-472
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