Field Information Modeling (FIM)™: Best Practices Using Point Clouds

Round 1

Reviewer 1 Report

The paper aims to address the problem of element assignments within the point cloud data capture methodologies. The author has comprehensively reviewed the state of the art and has proposed three possible algorithms to deal with inherent errors of the process. The author has established his point well, and therefore this reviewer would suggest the paper for direct publication.

The author, however, is encouraged by this reviewer to establish the problem with a slower pace within the introduction section, particularly, the paper will improve if the author establishes the difference between the two construction settings, namely with negligible errors and with errors construction setting with examples, and the specificity of each problem domain early on.

Author Response

Dear Reviewer,

Dear Reviewer,

I would like to thank you very much for taking the time to review the work and providing your constructive feedback on this manuscript. The revised manuscript is marked in highlights and you can also review all the changes by using the "Track Changes" command on your MS Word.

With kind regards,

Reza Maalek.

Reviewer 2 Report

Dear Author,

I have reviewed the technical note entitled "Field Information Modeling (FIM)™: Best Practices using Point Clouds". In my opinion it is a very good and practical paper but it needs revisions. Few of my remarks you are able to see below. 

Best regards.

Introduction.

In my opinion there is a need to extend the description about:

What methods did you use to show the best practices of creating FIM ?

What are these new alghorithms ?

What are the limitations of the study ?

Point Cloud Analysis

The ICP alghorithm is the most popular but also one of the oldest used in point cloud processing. There are new, more optimal methods. For example see #title: "PointNetLK: Robust & Efficient Point Cloud Registration using PointNet". I would like to suggest to see and compare these methods. 

There are also a methods of fitting which are crucial to compare f.e. RANSAC. With all of the difference methods, presented and compared there is a possibility to examine the robustness of the results. 

For me it is crucial to describe it, because without that description and comparison between methods I can see some method which could fit in a problem without presenting the whole spectrum of point cloud processing. 

Author Response

Dear Reviewer,

I would like to thank you very much for taking the time to review the work and providing your constructive feedback on this manuscript. I have attached a point by point response to your comments for your kind consideration. The revised manuscript is marked in highlights and you can also review all the changes by using the "Track Changes" command on your MS Word.

With kind regards,

Reza Maalek.

Author Response File: Author Response.pdf

Reviewer 3 Report

Review report
The document addresses the issue with solid foundations. Although a revision is recommended for its better understanding; some texts in the methodology section are very synthetic. They should be reviewed and completed to help the reader to understand properly.
Although the graphs are ideal to explain the methods, it is made of fewer images of Point Cloud typologies applied to real cases, as a reference to the different proposed methods.
The presentation of results should be accompanied by a chapter discussing the results, prior to the final conclusions.

Author Response

Response to Reviewer's Comments:

Comment 1: The document addresses the issue with solid foundations:

Response: Thank you for your acknowledgement of the solid foundation of my work.

Comment 2: Some texts in the methodology section are very synthetic. They should be reviewed and completed to help the reader to understand properly.

Response: The text in the methodology has been reviewed and to address your comment, the following modifications made (shown in blue highlights)

Lines 391-392: "The problem is solved using Algorithm 2: Point Cloud to Model Hypothesis Testing as follows:"

Lines 415-418: "Furthermore, the information regarding the distribution of the best fit parameters, such as covariance and mean of the distribution of the surface normal, can also be estimated during the process, which is shown to be an asset in systematically determining the correct threshold for surface segmentation [37]."

Comment 3: Although the graphs are ideal to explain the methods, it is made of fewer images of Point Cloud typologies applied to real cases, as a reference to the different proposed methods.

Response: Thank you for your acknowledgment on the ideal nature of the presented graphs in this study.

Comment 4: The presentation of results should be accompanied by a chapter discussing the results, prior to the final conclusions.

Response: thank you for your comment. Section 5: Discussion on Summary of Findings is added to the manuscript to address your comment. (Lines 582-615 of the revised manuscript).

Reviewer 4 Report

This paper deals with the current research topic of unstructured point cloud data within the BIM environment. The objective is to study different methods for mapping point cloud data onto the parts of the model that the data represent, This is studied in different field conditions in terms of construction errors.

The analysis of point clouds of the construction site against the project's BIM will clearly show the compliance between them. However, it should be explicitly clarified why the point clouds are transformed in this research.

Some other comments to improve the paper:

- The paper's structure should be revised. It is good to have the two scenarios (with or without construction errors) in different sections, but the results (and their discussion) should be placed in a (new) specific section before Conclusions. In its present form, the paper mixes the methods, the experimental setups and the results+interpretation+discussion.

- Given that different methods are tested, please include quantitative data in both the Abstract and Conclusions.

- Please cite any equipment used in this research (e.g. TLS devices, iPhone X).

- Figure 13 should be placed immediately after the paragraph where it is first mentioned.

LANGUAGE

Please check the correspondence of the number of the verb with the number of the subject.

E.g. lines 67-68 "In other cases, particularly when only 3D CAD models exists". Exist should be singular.

Line 343: "Construction errors is defined". It should be ARE defined.

Please check throughout the manuscript for this error.

Author Response

Dear Reviewer,

I would like to thank you very much for taking the time to review the work and providing your constructive feedback on this manuscript. I have attached a point by point response to your comments for your kind consideration. The revised manuscript is marked in highlights and you can also review all the changes by using the "Track Changes" command on your MS Word.

With kind regards,

Reza Maalek.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Thank you for addressing my comments.

Kind regards.