Abstract

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.

Highlights

  • Nowadays, due to advances in technology, generating of 2D and 3D products with significant geometric accuracy and detail, has become possible

  • The purpose of this paper is to identify the best software and sensors for generating a complete and accurate threedimensional model from small objects

  • After the mentioned stages for each object and each sensor, raw data is obtained. These raw data are run in various software and the point cloud for each object is achieved in three different sensors

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Summary

Introduction

Due to advances in technology, generating of 2D and 3D products with significant geometric accuracy and detail, has become possible. A detailed three-dimensional model for representation and documentation of different objects are needed in different branches of engineering.(Hess, Robson, & Hosseininaveh Ahmadabadian, 2014) Three-dimensional modelling of scenes and objects in different scales is performed using both image-based methods (passive) and range-based methods (active). Range-based or active methods (Vosselman & Maas, 2010) like structured light systems and laser scanner are common systems for point cloud generation. One of the most common algorithms in this field is SFM (Structure from Motion) algorithm (Agarwal et al, 2011). For this purpose, an archive of images of the object or scene is needed. One of the most commonly used operators in this operation is SIFT (Scale Invariant Feature Transform) (Fahmi, 2011) , which extracts identical features between images with different positions, scales and lighting

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