Perception of Risks and Usefulness of Smart Video Surveillance Systems
Round 1
Reviewer 1 Report
This article is about the perceived risks and usefulness of intelligent video surveillance (systems), as the title claims. However, the abstract states that the paper focuses on factors influencing the acceptance of privacy-friendly, smart video surveillance (system). So it goes from generality to specific case. They state that men rate risk concerning privacy significantly higher than women. They confirm such a claim in the present study. So this cannot be a contribution as claimed in Section 1.6!
The document repeats information in several paragraphs, like the introduction of Figure 1. In line 69, we read:
"An exemplary architecture for a system that would work as previously described is given in Figure 1."
then in line 84, we read:
"The description of the general workflow of the abnormality detection software is presented in Figure 1"
A reader should feel compelled to return since it is natural to think we overlook something. This kind of error appears in other parts of the document.
Authors base the study on previous work, which is fine, but they need to focus on the contribution of their work and not what was discovered by others. For example, men are more skeptical of perceived usefulness, investigating various public areas, or reports that women show more substantial acceptance of video surveillance than men. Other approaches are necessary than digital skeletons—analysis through censoring biometric features.
So the aim of the study seems poor:
"Are there gender differences, differences between public areas, and the time of day when visiting certain public areas"
Which is hard to read (use twice the word differences), but most importantly, is not clear the contribution.
or the following sentence
"Are there gender differences for different privacy levels of
smart video surveillance,"
It seems that it is already answered as exposed in the reviewed literature.
The authors present results using the Bonferroni test, which analyzes multiple comparisons, and it seems that this could be a contribution. However, even if we ask to rewrite the paper based on this point, I believe the contribution is weak for a journal paper. It is better to retake the research following other technological developments and compare three or more cases. Also, I recommend including the questionnaire so the reader can understand the assessment of the study.
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
This paper focuses on a very interesting area, human privacy, which is usually ignored by most artificial intelligence researchers. The authors carried out an online survey to investigate this issue. There are about 200 people took part in this survey. The results are a bit surprising that men pay more attention to privacy than women. Although there are some issues to be addressed, this is an interesting paper for both researchers and normal readers.
Issues to be addressed:
1. More details are need for the people who attended the survey, for example their nationality, education background, etc. This will largely impact the potential application scope of this paper.
2. Some recently emerged surveillance forms are ignored in the introduction, which heavily limited the level of the paper. These include unmanned aerial visual tracking (UAV), smart robots, face recognition, action recognition:
UAV:
The unmanned aerial vehicle benchmark: Object detection and tracking
Robust visual tracking via scale-and-state-awareness
Face Recognition:
Magface: A universal representation for face recognition and quality assessment
Siamese local and global networks for robust face tracking
Smart Robot:
Reverie: Remote embodied visual referring expression in real indoor environments
Touchdown: Natural Language Navigation and Spatial Reasoning in Visual Street Environments
The road to know-where: An object-and-room informed sequential bert for indoor vision-language navigation
HOP: History-and-Order Aware Pre-training for Vision-and-Language Navigation
Neighbor-view enhanced model for vision and language navigation
Action Recognition：
D3D: Dual 3-D convolutional network for real-time action recognition
High Performance Gesture Recognition via Effective and Efficient Temporal Modeling
BoMW: Bag of manifold words for one-shot learning gesture recognition from kinect
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
The titles of figures and tables are too long try to shorten them
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
I recommend to substitute references written in german for English literature. For example, you use 6 and 14 sometimes and and only 6 in another sentence when discussing about purpose in visual systems. There you can add a more suitable reference. Also, avoid using multiple references since the reader does not know which is better suited for your idea. Select one reference and if you want to include all of them then explain why you chose them and develop the idea while explaining each reference.
Author Response
Dear Reviewer 1,
please see the attached appendix (PDF-File).
Best regards
Thomas Golda, Deborah Guaia and Verena Wagner-Hartl
Author Response File: Author Response.pdf
Reviewer 3 Report
Accepted
Author Response
Dear Reviewer 3,
thank you for accepting our article "Perception of Risks and Usefulness of Smart Video Surveillance Systems" by Golda, T., Guaia, D., Wagner-Hartl, V., in Applied Sciences. We thank you very much for your suggestions and support.
If you have any questions, please do not hesitate to contact us.
Sincerely,
Thomas Golda, Deborah Guaia and Verena Wagner-Hartl
Author Response File: Author Response.pdf
