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Merge branch 'master' of https://git.frank-ebner.de/FHWS/IPIN2018

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tex_review/review/01_review.txt
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Dear Reviewer, Dear Reviewer,
-> At first we would like to start with a short overview over all changes. The individual answers follow directly after this text. All additions to the text are highlighted in blue. Words or text passages suggested by the reviewers to be removed are highlighted in red. As you will see, abstract and introduction are completely revised to better highlight the novel contributions. We were able to implement many suggestions of the reviewers. The transition was highly extended, to achieve a better understanding of the method. We have also added a detailed description of how and by what means our system is installed in a building. This also leads to a better description of the experimental setup. -> At first we would like to start with a short overview over all changes. The individual answers follow directly after this text. All additions to the text are highlighted in blue. Words or text passages suggested by the reviewers to be removed are highlighted in red. As you will see, abstract and introduction are completely revised to better highlight the novel contributions. We were able to implement many suggestions of the reviewers. The transition was highly extended, to achieve a better understanding of the method. We have also added a detailed description of how and by what means our system is installed in a building. This also leads to a better description of the experimental setup.
We added a complete new section, evaluating the activity recognition. Additionally, you will find mind smaller changes and addition throughout the paper as well as further improvements of the writing. In the following our answers are marked with "->". We added a complete new section, evaluating the activity recognition. Additionally, you will find many smaller changes and addition throughout the paper as well as further improvements of the writing. In the following our answers are marked with "->".
The paper presents a smartphone-based localization system using a particle filter to incorporate different probabilistic models. The comments and suggestions as follows: The paper presents a smartphone-based localization system using a particle filter to incorporate different probabilistic models. The comments and suggestions as follows:
@@ -24,13 +24,13 @@ The paper presents a smartphone-based localization system using a particle filte
5. The author mention that "Such buildings are often full of nooks and crannies, what makes it hard for dynamical models using any kind of pedestrian dead reckoning (PDR)","the error accumulates not only over time, but also with the number of turns and steps made". So "Thus, this paper presents a robust but realistic movement model using a three-dimensional navigation mesh based on triangles". However, Why does the three-dimensional navigation mesh can deal with the turns and steps error? The author should give the more detail description. The navigation graph uses 30*30 grid-cell, the navigation mesh uses triangles. But I don't find very clear that how does the triangles plan? More triangles can improve the accuracy or not? Why the the ground floor need 320 triangles? This the minimum? 5. The author mention that "Such buildings are often full of nooks and crannies, what makes it hard for dynamical models using any kind of pedestrian dead reckoning (PDR)","the error accumulates not only over time, but also with the number of turns and steps made". So "Thus, this paper presents a robust but realistic movement model using a three-dimensional navigation mesh based on triangles". However, Why does the three-dimensional navigation mesh can deal with the turns and steps error? The author should give the more detail description. The navigation graph uses 30*30 grid-cell, the navigation mesh uses triangles. But I don't find very clear that how does the triangles plan? More triangles can improve the accuracy or not? Why the the ground floor need 320 triangles? This the minimum?
-> We completely changed the transition part, describing how both, graph and nav-mesh are generated automatically, based on the building's floorplan. The number of required triangles strongly depends on the building's layout. 320 were required for the building presented within the picture. We hope that the revised chapter will be easier to understand and give clearer insights into the method, as it is a very important part of our system. -> We completely changed the transition part, describing how both, graph and nav-mesh are generated automatically, based on the building's floor plan. The number of required triangles strongly depends on the building's layout. 320 were required for the building presented within the picture. We hope that the revised chapter will be easier to understand and give clearer insights into the method, as it is a very important part of our system.
6. The authors emphasize that "The goal of this work is to propose a fast to deploy and low-cost localization solution, that provides reasonable results in a high variety of situations". But for the 2500m2 building they used 42 WiFi beacon. I don't think the number is few. Is the whole 42 beacon necessary? The author should discuss the impact of the number of WiFi beacon. How many are the reference poits? What's the impact of the density of the reference points? If the authors want to emphasizen the fast deploy and low-cost, they should give more detail discussion, also the "high variety". 6. The authors emphasize that "The goal of this work is to propose a fast to deploy and low-cost localization solution, that provides reasonable results in a high variety of situations". But for the 2500m2 building they used 42 WiFi beacon. I don't think the number is few. Is the whole 42 beacon necessary? The author should discuss the impact of the number of WiFi beacon. How many are the reference poits? What's the impact of the density of the reference points? If the authors want to emphasizen the fast deploy and low-cost, they should give more detail discussion, also the "high variety".
-> At first, "within the 2500m2 building" was a bad misformulation, as the building is far bigger. The 2500m2 refers only to the area that is actually walkable by the visitors. As can be seen in figure 7, the building has a very large courtyard in its center. A second reason for the high number of beacons, are the very thick walls. To prevent to much attenuation, we tried to install at least two beacons per room and a third one in an approximate radius of 10 meter. As said before, this was done very quickly without analyzing the Wi-Fi coverage. As the beacons are very cheap (less then $10), they represent only a small part of the total cost of the system. They only require a power source in order to operate, which keeps the need for additional infrastructure small. Furthermore, we believe that a janitor is able to set up our system independently. This means that there is no need to pay an external contractor to utilize the system and only the hardware costs and, if applicable, the price of the software have to be calculated. Nevertheless, these considerations could not apply to all buildings and scenarios, which is why the property "low cost" is removed. Please also refer to line 563 to 586. The number of reference points (133) was added to the text. The term "fast to deploy" is discussed in great detail at the beginning of the experiments. Experiments providing the impact of the density of the reference points, as well as the access-points can be found in our previous paper, "" -> At first, "within the 2500m2 building" was a bad misformulation, as the building is far bigger. The 2500m2 refers only to the area that is actually walkable by the visitors. As can be seen in figure 7, the building has a very large courtyard in its center. A second reason for the high number of beacons, are the very thick walls. To prevent to much attenuation, we tried to install at least two beacons per room and a third one in an approximate radius of 10 meter. As said before, this was done very quickly without analyzing the Wi-Fi coverage. As the beacons are very cheap (less then $10), they represent only a small part of the total cost of the system. They only require a power source in order to operate, which keeps the need for additional infrastructure small. Furthermore, we believe that a janitor is able to set up our system independently. This means that there is no need to pay an external contractor to utilize the system and only the hardware costs and, if applicable, the price of the software have to be calculated. Nevertheless, these considerations could not apply to all buildings and scenarios, which is why the property "low cost" is removed. Please also refer to line 563 to 586. The number of reference points (133) was added to the text. The term "fast to deploy" is discussed in great detail at the beginning of the experiments. Experiments providing the impact of the density of the reference points, as well as the access-points can be found in our previous paper, ""
-> Thank you again for your time and the good suggestions to further improve this work. -> Thank you again for your time and the detailed suggestions to further improve this work.

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tex_review/review/02_review.txt
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Dear Reviewer, Dear Reviewer,
-> At first we would like to start with a short overview over all changes. The individual answers follow directly after this text. All additions to the text are highlighted in blue. Words or text passages suggested by the reviewers to be removed are highlighted in red. As you will see, abstract and introduction are completely revised to better highlight the novel contributions. We were able to implement many suggestions of the reviewers. The transition was highly extended, to achieve a better understanding of the method. We have also added a detailed description of how and by what means our system is installed in a building. This also leads to a better description of the experimental setup. -> At first we would like to start with a short overview over all changes. The individual answers follow directly after this text. All additions to the text are highlighted in blue. Words or text passages suggested by the reviewers to be removed are highlighted in red. As you will see, abstract and introduction are completely revised to better highlight the novel contributions. We were able to implement many suggestions of the reviewers. The transition was highly extended, to achieve a better understanding of the method. We have also added a detailed description of how and by what means our system is installed in a building. This also leads to a better description of the experimental setup.
We added a complete new section, evaluating the activity recognition. Additionally, you will find mind smaller changes and addition throughout the paper as well as further improvements of the writing. In the following our answers are marked with "->". We added a complete new section, evaluating the activity recognition. Additionally, you will find many smaller changes and addition throughout the paper as well as further improvements of the writing. In the following our answers are marked with "->".
Overall: Overall:
@@ -30,7 +30,7 @@ line 226: What is z_t? Is an observation o_t? nomenclature should be unified thr
line 319: Are these thresholds able for all of pedestrians? have you tried with different actors and behaviors? line 319: Are these thresholds able for all of pedestrians? have you tried with different actors and behaviors?
-> Thank you very much for this suggestion. Based in it, we have added an evaluation of the activity recognition to the experiments, see chapter 7.4. We used the same measurement series (walk 0 - 3) as before. It was recorded by 4 different testers using 3 different devices. -> Thank you very much for this suggestion. Based on it, we have added an evaluation of the activity recognition to the experiments, see chapter 7.4. We used the same measurement series (walk 0 - 3) as before. It was recorded by 4 different testers using 3 different devices.
line 410: Why 10.000 samples in the building? Should it be dependent of the building size, wifi noise, etc...? line 410: Why 10.000 samples in the building? Should it be dependent of the building size, wifi noise, etc...?
-> Thanks for pointing that out, this was a misformulation and badly explained. We revised the paragraph accordingly. Please see line 502 to 519. -> Thanks for pointing that out, this was a misformulation and badly explained. We revised the paragraph accordingly. Please see line 502 to 519.
@@ -48,7 +48,7 @@ line 512: typo "prober"
Figure 5: It is not clear connections between ground floor and first floor, is there any typo or figures are misplaced? Figure 5: It is not clear connections between ground floor and first floor, is there any typo or figures are misplaced?
-> Thank you very much for pointing that out. As the building had various construction measures since the 13th century, its architecture is rather hard to understand. We revised the figure (now figure 8) by adding numbers to the stairs involved. We hope this gives a better understanding of the buildings respective floors. -> Thank you very much for pointing that out. As the building had various construction measures since the 13th century, its architecture is rather hard to visualize. We revised the figure (now figure 8) by adding numbers to the stairs involved. We hope this gives a better understanding of the buildings respective floors.
Figure 6: You use the expression "Monte Carlo", are you referring to Condensation? Figure 6: You use the expression "Monte Carlo", are you referring to Condensation?
-> Yes, we are referring to a single run of the CONDENSATION particle filter. We fixed it accordingly. -> Yes, we are referring to a single run of the CONDENSATION particle filter. We fixed it accordingly.
@@ -57,5 +57,5 @@ Results section: results and comments are ad-hoc for this environment, and it is
-> We incorporated this suggestion into the conclusion section of this work. Please see line 956 to line 959. However, we have decided not to discuss the general usage of this approach in the experiments, since this work explicitly deals with a historical building. -> We incorporated this suggestion into the conclusion section of this work. Please see line 956 to line 959. However, we have decided not to discuss the general usage of this approach in the experiments, since this work explicitly deals with a historical building.
-> Again, thank you very much for your time and the good suggestions. They further improved this work. -> Again, thank you very much for your time and the detailed suggestions. They further improved this work.

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tex_review/review/03_review.txt
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Dear Reviewer, Dear Reviewer,
-> At first we would like to start with a short overview over all changes. The individual answers follow directly after this text. All additions to the text are highlighted in blue. Words or text passages suggested by the reviewers to be removed are highlighted in red. As you will see, abstract and introduction are completely revised to better highlight the novel contributions. We were able to implement many suggestions of the reviewers. The transition was highly extended, to achieve a better understanding of the method. We have also added a detailed description of how and by what means our system is installed in a building. This also leads to a better description of the experimental setup. -> At first we would like to start with a short overview over all changes. The individual answers follow directly after this text. All additions to the text are highlighted in blue. Words or text passages suggested by the reviewers to be removed are highlighted in red. As you will see, abstract and introduction are completely revised to better highlight the novel contributions. We were able to implement many suggestions of the reviewers. The transition was highly extended, to achieve a better understanding of the method. We have also added a detailed description of how and by what means our system is installed in a building. This also leads to a better description of the experimental setup.
We added a complete new section, evaluating the activity recognition. Additionally, you will find mind smaller changes and addition throughout the paper as well as further improvements of the writing. In the following our answers are marked with "->". We added a complete new section, evaluating the activity recognition. Additionally, you will find many smaller changes and addition throughout the paper as well as further improvements of the writing. In the following our answers are marked with "->".
The paper presents an improvement to a previous work of the authors where a transition, model, an activity recognition method, a recovery method for the particle filter, and an improved density estimation. The paper presents an improvement to a previous work of the authors where a transition, model, an activity recognition method, a recovery method for the particle filter, and an improved density estimation.
@@ -13,8 +13,7 @@ The novelty of the paper was collected in the reading and it should be more clea
The rapid computation declaration is not proven, given that the authors do not compare the non-gridded approach timings. The rapid computation declaration is not proven, given that the authors do not compare the non-gridded approach timings.
-> The terminology "rapid computation scheme" only refers to the state estimation process, not the underlying mesh or the complete system performance. It seems this was not clearly formulated within the paper. Thanks for pointing that out. We tried to clarify this in different parts of the work, especially in the introduction. We also removed the terminology "rapid computation" and instead called it "approximation" scheme. -> The terminology "rapid computation scheme" only refers to the state estimation process, not the underlying mesh or the complete system performance. It seems this was not clearly formulated within the paper. Thanks for pointing that out. We tried to clarify this in different parts of the work, especially in the introduction. We also removed the terminology "rapid computation" and instead called it "approximation" scheme.
For clarification, the weighted-average estimator yields faster estimates of the position compared to the KDE approach as we have shown in our previous work "Fast Kernel Density Estimation using Gaussian For clarification, the weighted-average estimator yields faster estimates of the position compared to the KDE approach as we have shown in our previous work "Fast Kernel Density Estimation using Gaussian Filter Approximation". This previous work does also provide an extensive comparison between other state-of-the-art KDE approximations.
Filter Approximation". This previous work does also provide an extensive comparison between other state-of-the-art KDE approximations.
Does the system will also work in regular buildings? A final comment on the lessons learned in this case of the 13th century building should be in the conclusions, given that the title focus on this very specific context. Does the system will also work in regular buildings? A final comment on the lessons learned in this case of the 13th century building should be in the conclusions, given that the title focus on this very specific context.
@@ -89,8 +88,7 @@ Ln 237: "...the average acceleration..." This includes both linear acceleration
Ln 258 - This equation needs revision. Should it be "p(s_i|p) ~ N(u_i,p , std²_wifi)" ? Also the wall-attenuation-factor-model only takes into account attenuation by floors, not walls. Ln 258 - This equation needs revision. Should it be "p(s_i|p) ~ N(u_i,p , std²_wifi)" ? Also the wall-attenuation-factor-model only takes into account attenuation by floors, not walls.
-> The equation is correct. Its the actual >result< of the normal distribution when questioned for the received s_i, given the model prediction was u_i,p with uncertainty \sigma^2_wifi. -> The equation is correct. Its the actual >result< of the normal distribution when questioned for the received s_i, given the model prediction was u_i,p with uncertainty \sigma^2_wifi.
-> We now made clear that our model is something in between the log-distance and the wall-attenuation factor model. To reduce computation time on the smartphone, only floors/ceilings are considered -> We now made clear that our model is something in between the log-distance and the wall-attenuation factor model. To reduce computation time on the smartphone, only floors/ceilings are considered as this can be achieved without costly intersection tests. We also pointed out, that including walls would be more accurate, but is costly during runtime (intersection-tests).
as this can be achieved without costly intersection tests. We also pointed out, that including walls would be more accurate, but is costly during runtime (intersection-tests).
Ln 271-272: The authors mention that their WiFi fingerprinting approximation process is faster than classical fingerprinting, but they fail to provide a reference for an example of the latter or significant metrics such as the average time per square meter for fingerprinting a whole building. Furthermore, the authors should also take into account that while there are approaches where reference measurements are recorded on small grids between 1 to 2m, there are also approaches able to record reference measurements using faster methods. One example is walking by the building while registering ground truth points and using dead reckoning techniques (see Guimarães, V. et al. A motion tracking solution for indoor localization using smartphones. In Proceedings of the 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN)). Ln 271-272: The authors mention that their WiFi fingerprinting approximation process is faster than classical fingerprinting, but they fail to provide a reference for an example of the latter or significant metrics such as the average time per square meter for fingerprinting a whole building. Furthermore, the authors should also take into account that while there are approaches where reference measurements are recorded on small grids between 1 to 2m, there are also approaches able to record reference measurements using faster methods. One example is walking by the building while registering ground truth points and using dead reckoning techniques (see Guimarães, V. et al. A motion tracking solution for indoor localization using smartphones. In Proceedings of the 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN)).