Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 515-519, 2015
https://doi.org/10.5194/isprsarchives-XL-1-W5-515-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
11 Dec 2015
THE PERFORMANCE EVALUATION OF MULTI-IMAGE 3D RECONSTRUCTION SOFTWARE WITH DIFFERENT SENSORS
V. Mousavi, M. Khosravi, M. Ahmadi, N. Noori, A. Hosseini Naveh, and M. Varshosaz K.N.Toosi University of Tecknology, Faculty of Surveying Engeeniring, Tehran, Iran
Keywords: Sensor, software, Image-based 3D reconstruction, Data comparison, point cloud, three-dimensional model Abstract. Today, multi-image 3D reconstruction is an active research field and generating three dimensional model of the objects is one the most discussed issues in Photogrammetry and Computer Vision that can be accomplished using range-based or image-based methods. Very accurate and dense point clouds generated by range-based methods such as structured light systems and laser scanners has introduced them as reliable tools in the industry. Image-based 3D digitization methodologies offer the option of reconstructing an object by a set of unordered images that depict it from different viewpoints. As their hardware requirements are narrowed down to a digital camera and a computer system, they compose an attractive 3D digitization approach, consequently, although range-based methods are generally very accurate, image-based methods are low-cost and can be easily used by non-professional users. One of the factors affecting the accuracy of the obtained model in image-based methods is the software and algorithm used to generate three dimensional model. These algorithms are provided in the form of commercial software, open source and web-based services. Another important factor in the accuracy of the obtained model is the type of sensor used. Due to availability of mobile sensors to the public, popularity of professional sensors and the advent of stereo sensors, a comparison of these three sensors plays an effective role in evaluating and finding the optimized method to generate three-dimensional models. Lots of research has been accomplished to identify a suitable software and algorithm to achieve an accurate and complete model, however little attention is paid to the type of sensors used and its effects on the quality of the final model. The purpose of this paper is deliberation and the introduction of an appropriate combination of a sensor and software to provide a complete model with the highest accuracy. To do this, different software, used in previous studies, were compared and the most popular ones in each category were selected (Arc 3D, Visual SfM, Sure, Agisoft). Also four small objects with distinct geometric properties and especial complexities were chosen and their accurate models as reliable true data was created using ATOS Compact Scan 2M 3D scanner. Images were taken using Fujifilm Real 3D stereo camera, Apple iPhone 5 and Nikon D3200 professional camera and three dimensional models of the objects were obtained using each of the software. Finally, a comprehensive comparison between the detailed reviews of the results on the data set showed that the best combination of software and sensors for generating three-dimensional models is directly related to the object shape as well as the expected accuracy of the final model. Generally better quantitative and qualitative results were obtained by using the Nikon D3200 professional camera, while Fujifilm Real 3D stereo camera and Apple iPhone 5 were the second and third respectively in this comparison. On the other hand, three software of Visual SfM, Sure and Agisoft had a hard competition to achieve the most accurate and complete model of the objects and the best software was different according to the geometric properties of the object.
Conference paper (PDF, 1049 KB)


Citation: Mousavi, V., Khosravi, M., Ahmadi, M., Noori, N., Hosseini Naveh, A., and Varshosaz, M.: THE PERFORMANCE EVALUATION OF MULTI-IMAGE 3D RECONSTRUCTION SOFTWARE WITH DIFFERENT SENSORS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 515-519, https://doi.org/10.5194/isprsarchives-XL-1-W5-515-2015, 2015.

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