Automation in Construction 33 (2013) 104–115

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Automation in Construction

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An invisible head marker tracking system for indoor mobile augmented reality

Chyigang Kuo a,⁎, Taysheng Jeng b, Itung Yang c

a Dept. of Architecture, Chaoyang Univ. of Technology, Taiwanb Dept. of Architecture, National Cheng Kung Univ., Taiwanc Dept. of Construction Engineering, National Taiwan Univ. of Science and Technology, Taiwan

⁎ Corresponding author. Tel.: +886 933067607; fax:E-mail addresses: chyigang@cyut.edu.tw (C. Kuo), ts

(T. Jeng), ityang@mail.ntust.edu.tw (I. Yang).

0926-5805/$ – see front matter © 2012 Elsevier B.V. Allhttp://dx.doi.org/10.1016/j.autcon.2012.09.011

a b s t r a c t

a r t i c l e i n f o

Article history:Accepted 29 September 2012Available online 13 November 2012

Keywords:Augmented realityIndoor positioningMobile position trackingInvisible marker

This research aims to develop a mobile augmented reality positioning system for indoor construction appli-cation by tracking the coordinates of the user and their angles of vision so as to realize three-dimensionalindoor positioning with high environmental adaptability.This research uses infrared invisible marker identification technique, and adopts the outside–in trackingmode to develop the Head Marker Tracking Augmented Reality (HMTAR) system, which can be mountedindoors or outdoors and has the extensive tracking capability, event memory mechanism, and scenario shar-ing mechanism. Evaluation results were obtained from Heuristic Evaluation and SUS evaluation. The resultsdemonstrated a prospect for indoor augmented reality positioning technique.

© 2012 Elsevier B.V. All rights reserved.

1. Introduction

The ever-advancing Augmented Reality (AR) is gaining extensiveapplications in the construction field: such as, real-time 3D display ofon-site construction progress [1], introduction of objects assemblingprocedures [2], 3D explanation of construction principle [3,4], remotesimulation of construction tools' operation [5], design and revitalizationin existing built environments [6] andmany others. Among these cases,actual outdoor applications are mostly GPS-based tracking systems.However, the positioning errors and unreachability to indoor area ofGPS signals have limited GPS-based AR application to outdoor fixedpoint control or merely for longer distance observation without provid-ing close-range mobile operation. On the other hand, most indoor ARtracking systems are marker-based systems which have certainfunctional limitations too, namely, visual environmental impact due tothe marker's high black-and-white contrast, and marker-restrictedenvironments (including constructions with no continuous flat surface,structures at historic site, unsuitable construction surface materials,water surface and mid-air prohibited from posting marker). It can beseen, therefore, that by solving the above-mentioned drawbacks of ARpositioning systems, the overall AR application to the constructionfield can be increased to a greater extent. With this in mind, the studyproposes a new mode for indoor construction application by summingup the advantages and disadvantages of the existing positioningtechniques, and rethinking of trouble-shooting to those obstacles.

+886 4 23742339.jeng@mail.ncku.edu.tw

rights reserved.

2. Analysis of AR position techniques for construction applications

Among all positioning techniques, Bhatnagar [7] has targeted fourcategories: mechanical, optical, ultrasonic and electro-magnetic in hisrating of HMD (Head Mounted Display) positioning techniques. Inaddition to these four categories, other two categories: marker track-ing [8–10] and natural feature tracking [11–14] are added to form amore complete picture of positioning techniques and applied tech-nologies, as shown in Table 1.

Ratings of such positioning techniques have been seen in manyprevious related literatures. One prominent example is Gu and hiscolleagues, in “A Survey of Indoor Positioning Systems forWireless Person-al Networks,” [15] have proposed 8 criteria from 17 existing positioningdevices both on market and under R&D: (1) Security and Privacy;(2) Cost; (3) Performance; (4) Robustness; (5) Complexity; (6) UserPreferences; (7) Commercial availability; and (8) Limitations.

Focusing on the “accuracy” criterion, Institute of Geodesy andPhotogrammetry, Swiss Federal Institute of Technology has integrat-ed the detection range and relative accuracy of various positioningtechniques [16]. As shown in Fig. A.1, Appendix A, mechanical posi-tioning has the highest accuracy, followed by optical tracking (includ-ing vision-based ProCam, Laser Tracker, and IGPS), and ultrasonic.Electro-magnetic (UWB, RFID, WLAN/Wi-Fi, AGPS and GSM) has thelowest accuracy.

In recent years, rapid development of natural feature trackingtechniques, especially the most advanced marker-free PTAM [17],with its high mobility, greater tracking accuracy, free software library,and adaptability to indoor and outdoor applications, have basicallymet almost all the application requirements of AR systems. However,Lex van der Sluijs indicates that in large open spaces, where there is alarge distance between the viewer and the nearest visual detail, the

Table 1Positioning techniques and applied technologies.

Positioning techniques Applied technology

1. Mechanical tracking Robot arm, force feedback device2. Ultrasonic tracking Ultrasound waves (person positioning/spatial

scanning)3. Optical tracking Infrared rays, leaser, iGPs (person positioning/spatial

scanning); target ball tracking, eyeball tracking4. Electromagnetic

trackingGPS, DGPS, AGPS, TV-GPS, UWB, WAAS, RF,Bluetooth, ZigBee, RuBee

5. Marker tracking Marker recognition and hidden marker recognition6. Natural feature tracking PTAM (MonoSLAM), PTAMM, BazAR

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user has to move a large amount to even be able to begin visual track-ing [18]. Also, in many buildings there are many self-similar locations.So if tracking is lost and has to be re-initialized, this is a problem if ithas to happen based on visual clues alone [18]. This is especially truewith initial indoor construction environment where only repeatedsimilar structures and large space exist.

Meanwhile, re-scanning of feature points and reloading of virtualobjects will be required to ensure displaying of AR images in thePTAM system when constructs, interior decorations or furniture arelocated in or removed from indoor construction environment. Suchproblems could possibly occur to indoor construction site with ARsystem of inside–out positioning technique, and probably this iswhere outside–in positioning techniques could be set in.

Outside–in positioning techniques include ultrasonic tracking[19], electro-magnetic tracking [20,21], and optical tracking [22–24],with optical tracking having the highest positioning accuracy [16].

One of the most advanced optical tracking systems, Iotracker [23],is capable of conducting a 6-DOF (Degree of Freedom) positioning in aprepared environment. Nevertheless, the overly long path spanningbetween transmitting and receiving the IR rays subject the Iotrackerto the interferences from surrounding thermal radiation and otherIR rays, making the environmental light a very demanding condition.Meanwhile, although Iotracker allows simultaneous positioning bymultiple users, the function is limited to the close similarity betweenthe reflective target balls. To avoid mutual disturbance caused by thetarget balls, an IR camera is installed above each user for tracking pur-pose [25], provided that no user makes arbitrary moves into thefield-of-view of other camera. This is the obstacle that Iotrackerneeds to overcome.

The above case analysis leads us to conclude that the trackingtechnique for an AR system equipped in the indoor construction envi-ronment is suggested to have the following features: (i) outside–intracking mode; (ii) 6DOF mobile tracking ability; (iii) adaptability tolow illumination environment; (iv) maneuverability at a variety ofterrains; (v) posing less obstruction to construction progress; and(vi) lower impact on the positioning capability from surroundingconstruction changes.

3. System establishment

To achieve the goals, the study proposes HMTAR (Head MarkerTracking Augmented Reality) system. HMTAR is an outside–invision-based tracking system. By applying an opposite manner, itsfully developed marker tracking techniques is thus transformed intoa new position tracking system targeting the user's headset. Withthe satellite cameras installed in the environment, the system can de-tect the coordinates and rotation direction of user's head markers toperform real-time 6-DOF positioning tracking. The system can bemaneuverably installed at various terrains, and the virtual objectscan be positioned without placing any marker in the space.

HMTAR system comprises a position detection module (executedby AREyeSatellite program packet) and a mobile display module (ex-ecuted by AREyeCenter package) (Fig. 1 left).

The position detection module consists of computer sets and USBIR webcams. No expensive hardware equipments are required. Toconduct virtual object display calculation, first connect one set or sev-eral sets of satellite cameras (USB IR webcams) to a computer set.Each computer set then wirelessly transmits the detected positioningdata to the server, which then transfers the integrated positioningdata to user's laptop computer (Fig. 1 right).

The mobile display module includes a positioning headset, and atransparent and ventilating functional backpack (Fig. 2). The headsetis all black under naked eyes, but its invisible Eye Markers emergeunder IR webcams (Fig. 3). The headset enables a multi-marker de-tection, to ensure that at least one side-marker can be detected bythe satellite camera when user travels, rotates, or bends or lifts his/her head. Meanwhile, the headset uses a self-illuminating IR lightsource to reduce the IR rays travel distance and to enhance thesystem's resistance to the disturbance from ambient lights (Fig. 4).Moreover, the IR positioning capability enables HMTAR to functionin dark environments.

Internal IR LED module; (right) EyeCamera attached to the head-set brim to provide a first person AR view to the user (model:GoodTec My Cam, USB 2.0, maximum 8 mega pixels).

The core code of HMTAR is constructed on FLARToolKit, dividedinto seven modules, as shown in the following Fig. 5:

(i) FMS Module: Memorizing Satellite Camera's own coordinateinformation under Flash Media Server, receiving user's EyeMarker and auxiliary Target Marker coordinate information,and managing coordinate information generated by CenterModule.

(ii) Center Module: Installed on user's laptop for receiving EyeMarker positioning information transmitted by FMS, and com-puting 3D models generated by PV3D. Additional computing ofPath RecodingModule and Video Recording Module is requiredwhen ARPlayer is ON.

(iii) FLARToolkit Module: The core code of the system installedon user's laptop for calculating maker information detectedby Satellite Camera and 6DOF movement coordinates byFlarDetector.

(iv) Satellite Module: Detecting Marker image, adjusting errors,integrating mean values, and transmitting the detected in-formation to FMS Module.

(v) PV3D Module: Installed on user's laptop for generating 3Dobjects and rendering materials according to received coor-dinate information, and providing icon drawing functions.

(vi) Path Recording Module: When ARPlayer is ON, it can recorduser's 6DOF path coordinate information.

(vii) Video Recording Module: When ARPlayer is ON, it can re-cord user's viewed image information.

In case user's motion exceeds the first satellite camera's visualfield, another satellite camera next in line can take over to form a3D positioning array, where visible range and heights can expand.Preferably a zigzag array can be adopted to form a recognition areawithout any blind spots. Or alternately, a diametric array is adoptedto gain the largest recognition range (Fig. 6).

After starting the system, the user holds the wireless mouse to

click / buttons to add/remove virtual objects in the view of

HMD (Fig. 7 left). Click “FollowMe” or “FollowMarker” to position se-lected object. Drag the handlebars on the left to control motion drift,rotation and “Smooth” display of the virtual object.

By first clicking FollowMe, followed by loading 3D virtual object,the loaded 3D object is then positioned in the center of the user'shead. The 3D object will move away from the user until it reaches1 M of user's front when the bar on the right bottom is pushed tothe far right end (Fig. 7, left). By shifting to Free, location of the virtualobject is fixed.

Fig. 2. Components of mobile display module. The user wears the i-Visor FX601HMD to watch the AR view.

Fig. 1. (left) Positioning principle framework. (right) Hardware construct of positioning detection module.

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Or alternatively, place a custom-made hexahedron – Target Mark-er (Fig. 7 right) – on the desired position of the 3D object. Then checkFollowMarker. 3D object will display on the Target Marker. Whenshifted to Free, the 3D object will be positioned and will not disappearwhen the Target Marker is later removed.

HMTAR is capable of recording the whole process of AR dynamicframes, and memorizing the path, rotation and angular parametersof the user's head movements (6-DOF parameters). Thus, all previous

Fig. 3. An all-black Eye Marker under naked eyes (left); distinctive black-and-white positiondisplayed on the screen (right).

Fig. 4. Structure and components of the headset: (left) light metal body structure of the heato provide a first person AR view to the user (model: GoodTec My Cam, USB 2.0, maximum

traveling trails can be cued by Map, Path, and Follow modes duringlater replay (Fig. 8).

A remote control agent device equipped with IP cam allows theuser to generate AR frame by loading, deleting, or adjusting the 3Dvirtual objects with the operating mode exactly identical to theon-site operating mode (Fig. 9). Since the remote control of theagent device can be co-shared by multiple end-users, co-creation ofthe remote AR images is thus possible.

ing marker shown under IR camera (middle); recognized markers and positioning data

dset; (middle) internal IR LED module; (right) EyeCamera attached to the headset brim8 mega pixels).

Fig. 5. The code framework of HMTAR.

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4. Evaluations and discussions

4.1. Positioning accuracy

HMTAR's core framework is based upon FLARToolKit. Under thesame hardware specifications and environmental conditions, initialpositioning accuracy of the system should equal to that of theARToolKit. Related literature on ARToolKit positioning accuracy can

Fig. 6. Deployments of two

be found in the related researches [26,27], and ARToolKit officialsite [28]. Positioning accuracy of ARToolKit differs with factors suchas icon sizes, recognition distance, angle, etc. Although no resolutionrequirements are mentioned in the studies [26], it surely will be help-ful that a camera equipped with high resolution, auto focus, autowhiteness balance, low illumination compensation, and back lightcompensation is adopted for long-distance recognition, dynamic rec-ognition and environment with constant light changes. Therefore,

satellite camera arrays.

Fig. 7. (left) AR screen showing loading and setting of virtual object. (right) Target Marker.

Fig. 8. The control panel of recording and replaying AR frames.

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rather than only performingwell under a specific environmental condi-tion with fixed positioning accuracy, HMTAR is created with adjustablefeature to keep best accuracy under different lighting environments andoperational conditions.

Firstly, HMTAR is capable of adjusting the initial positioningaccuracy. The 6 DOF data and estimated distance (DIST) of EyeMark-er (or Target Marker) are shown on top (and bottom) of the serverscreen. By shifting the “Zoom” value, the estimated marker sizeratio could be calibrated; therefore the DIST value can be adjustedto match the real measured distance of Eye Marker or Target Marker(Fig. 10).

However during the practical operation, HMTAR's recognitionperformance, with its invisible marker recognition method, is

Fig. 9. 3D Virtual Object motions in sync with t

unavoidably affected by the lightwave decayed over distance.Other factors like IR Camera's limited resolution, differences of IRCamera's focus, different environmental lightings reflected by theblack material of headset, and visual nebulization of aerial suspen-sion particles, also cause instant-by-instant minor differences inthe invisible marker's recognition data. This in turn results in thejerking of virtual objects.

To overcome this phenomenon, secondly HMTAR has added aSmooth value, that is, a mean value is gained by calculating many co-ordinates generated by IR Camera and transmitted to PV3D for thevirtual object's coordinates. In other words, the larger the Smoothvalue adjustment, the larger the amount of mean values that canbe fed to the system for calculation. And the smaller difference

he rotation of the remote controlled agent.

Fig. 10. (left) The initial accuracy adjusting process of HMTAR; (middle) the 6 DOF data and estimated distance (DIST) of Eye Marker and Target Marker are shown on top and bot-tom of server screen; (right) the DIST value can be adjusted by dragging the “Zoom” bar in the server screen to match the real measured distance of Eye Marker or Target Marker.

Fig. 11. The locations of the three IR webcams in the exhibition hall.

Fig. 12. The testing process of HMTAR by Engineer Chen (upper left), Engineer Wang (upper right), Engineer Chang (lower left) and Engineer Huang (lower right).

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Table 2Average scores of HMTAR on Heuristic Evaluation.

No. Evaluation criteria Average scores

1 Visibility of system status 4.752 Match between system and real world 4.503 User control and freedom 4.254 Consistency 4.255 Error strategy 3.756 Recognition rather than recall 4.507 Flexibility and efficiency of use 3.758 Esthetics and minimalist design 3.759 Help users recognize, diagnose, and recover from errors 3.0010 Help and documentation 3.50

Table 3SUS evaluations of HMTAR.

Scores 1 2 3 4 5

What is your subjectivefeeling towards thesystem?

Stronglydisagree

Disagree Nocomment

Agree Stronglyagree

Number of person

1. I think that I would like touse this systemfrequently.

0 0 4 31 5

2. I found the systemunnecessarily complex.

1 28 7 4 0

3. I thought that the systemwas easy to use.

0 1 4 26 9

4. I think that I would needthe support of a technicalperson to be able to usethis system.

0 0 1 21 18

5. I found that the variousfunctions in this systemwere well integrated.

0 3 10 19 8

5. I thought that there wastoo much inconsistency inthis system.

33 7 0 0 0

7. I would imagine that mostpeople would learn to usethis system very quickly.

0 8 14 18 0

8. I found the system verycumbersome to use.

12 26 1 1 0

9. I felt very confident inusing the system.

0 7 18 10 5

10. I needed to learn a lot ofthings before I could getgoing with this system.

4 30 6 0 0

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betweenmean values can lessen the jerking movement of the virtualobject.

Furthermore, we have found that Smooth value is insufficient instabilizing the jerking virtual object. This is because Smooth value isused as a positioning value by averaging many coordinate values.Even when the Smooth value is adjusted to its maximum, the jerkingstill exists, only reduced to a slower motion. So much so that a slowjerking can be witnessed even when the user stands still.

To tackle this obstacle, thirdly we have added a Bound Displace-ment Segament Valve, to allow a freehand to the user for UP/DOWN settings. During the initial positioning, the system will targetthe first coordinate parameter as a baseline value, and then using thisbaseline value to mark the UP/DOWN settings. In the following coor-dinate recognition process, only those exceeding the UP/DOWN set-tings among all coordinate values are selected as new parameters orthe baseline value of the second coordinate. In this way, we can elim-inate the minor recognition errors and the 3D virtual object will notmake random jerking when the user stands still. Besides, the systemcan keep up with the speed and increases the stability of the 3D vir-tual object by making more sensitive response when the user makeslarger movement.

HMTAR is capable of reaching its optimal effect when the combinedBound and Smooth values are adjusted according to different environ-mental condition requirements. The codes of HMTAR about smoothand bound are listed in Appendix B.

To further enhance stability of the 3Dvirtual object displaying on theAR screen, the followingmechanisms are incorporated: satellite cameraperspective/focal length setup, satellite camera whiteness balance,brightness, contrast and other digital parameter controls, black headsetinternal IR LED brightness linear modulation.

Fig. 13. Students are

The seeming similarity between HMTAR and the improvedmarker tracking system, Intersense IS-1200 [29], are actually twoentirely different operational concepts. Intersense IS-1200, belong-ing to the family of inside–out AR system, requires many contrastingblack-and-white markers posting on the ceiling. Besides causing vi-sual impact, it also fails to function normally at construction siteswith no ceiling, complex roof structure and darker area or wheremarker is unsuitable, such as historic sites. Moreover, the postedmarkers will obstruct the construction process. All defects maintainedabove will relatively reduce the system's adaptability in the indoor con-struction sites.

testing HMTAR.

Fig. 14. The pre-positioned virtual 3D object in the AR view of HMTAR.

Fig. 15. Line-of-Sight interactive interface control mode.

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4.2. Evaluations

To verify HMTAR system's usability, four AR experts (Chen, Engineerat Human and Computer Interaction Center, National Industrial Tech-nology Research Institute; Wang, Engineer at Pitotech Co., Ltd.; Chang,Engineer at Pitotech Co., Ltd.; and Huang, Engineer at PolygonWorksCo., Ltd.) were invited to conduct Heuristic Evaluation [30,31]. Threefixed satellite IR cameras are installed at the experiment site (ExhibitionHall, 7th floor, Design Institute Building of ChaoyangUniversity of Tech-nology) (Figs. 11 and 12).

The four evaluators were guided to load a 3D object positioning at1 M ahead and then walk around to view it. The evaluators can freelyadjust the 6 DOF of the 3D object, even remove and add the objectinto AR view again. After the operation, four evaluators were asked tomake an assessment based on 10 criteria of Heuristic Evaluation. Evalu-ation scoreswere divided into 5 scales: “Absolutely not,” 1 point, “Most-ly not,” 2 points, “May be,” 3 points, “Mostly yes,” 4 points, “Absolutelyyes,” 5 points. Final results are shown in Table 2.

The assessment result indicates that the system has reached aboveaverage usability requirement. For construction application, HMTARhas ability to help designer present and position 3D virtual objects atsite, so that workers can follow the 3D images to perform the construc-tion task intuitively. However the lowest ratings in the evaluation fall ontwo items: “Help users recognize, diagnose, and recover from errors”and “Help and documentation,” indicating that some auxiliary func-tions, such as “reset” or “help” functions, designed to help users operatethe system remains to be strengthened.

Additionally, 40 students without AR system operating experiencefrom Architecture Department and Interior Design Department wereasked to simulate as visitors to the Design Gallery of CYUT to conductSUS assessments for HMTAR (Fig. 13).

SUS (System Usability Scale) was developed in 1986 by the BritishDigital Equipments Co., Ltd. to help business understand product'sease of use, and as a comparison model to the last generation productor competitor's product. It's a frequently adopted subjective perceptionscale for product's ease of use [32]. The SUS questionnaire, comprising10 questions, is a cross-inquiring, 5-point Likert Scale, ranging from 1(Strongly disagree) to 5 (Strongly agree) (Table 3). Calculation formu-la (1) [32] is as follows, wherein, S stands for item number. Totalscore ranges from 0 to 100, with the calculation value in positive corre-lation to the system's usability.

S1þ S3þ S5þ S7þ S9ð Þ−5½ � þ 25− S2þ S4þ S6þ S8þ S10ð Þ½ �f g� 2:5: ð1Þ

For evaluating HMTAR, the students were asked to wear the systemwalking along a path back and forth, squat and stand up twice, andtouch the pre-positioned virtual 3D objects around the gallery (Fig. 14).Each student only has 6 min to complete the actions, and then completesthe SUS questionnaire. The purpose of the actions is to explore andsimulate workers' feeling while equipped with HMTAR to view andstudy the task at construction site. The evaluation results areshown in Table 3.

Overall SUS evaluation reaches a value of 66.75, indicating a mod-erate to high level easy of use of HMTAR. According to the evaluationresult, HMTAR might be helpful to inexperienced workers to under-stand the task process or final result in 3D on precise location, in-stead of reading task information from the construction drawing bythemselves at the construction site.

5. Conclusions and future works

5.1. Conclusions

The study addresses the issue of which AR positioning technique ismost adoptable for indoor construction application. Based on the out-side–in tracking mode, this study has developed HMTAR system, to

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simultaneously recognize user's coordinates and vision direction byemploying IR invisible marker tracking technique. Since there is noneed to place markers in the physical space, the high environmentaladaptability feature allows the system to position virtual objects atthe desired location, including mid-air, water surface, above flame,or even out field-of-vision, as suitable to ever-changing constructingsites. The headset of the system uses a self-illuminating IR lightsource to reduce the IR rays' travel distance and to enhance thesystem's resistance to the disturbance from ambient lights. Moreover,the IR positioning capability enables HMTAR to function in dark con-struction environments. Equipped with array extension positioningcapability, the system can be installed (stationed and mobile) in in-door or outdoor continuous space.

A total of 6 mechanisms have been constructed in HMTAR to en-hance positioning accuracy and image stability of the 3D virtual ob-jects, including 1) marker ratio calibration (Zoom value), 2) smoothvalue, 3) bound value, 4) satellite camera perspective/focal lengthsetup, 5) satellite camera whiteness balance, brightness, contrastand other digital parameter controls, and 6) black headset IR LEDbrightness linear modulation.

Heuristic Evaluation of HMTAR yields a mean value of 4 (mostitems score >3 points), demonstrating a high usability. S valueresulted from evaluation of SUS is 66.75, indicating a moderate tohigh level easy of use perceived by the test subjects. The results ofthe two evaluations show that HMTAR could easily be operated bydesigners to position 3D virtual objects and by workers to exploreand study construction task process and final results at constructionsite.

Although applying FLARToolkit library to construct the executioncodes, HMTAR is created under outside–in tracking mode, which istotally different from all conventional inside–out tracking modeFLARToolkit applications whose posted markers will cause visual im-pact to the environment, obstruct the construction process, and fail tofunction normally at construction sites where marker is unsuitable.

Fig. A.1. Detection range and relative accur

Appendix A

Swiss Federal Institute of Technology has surveyed the detection rang

5.2. Future works

HMTAR is capable of positioning user's eye coordinates and visu-al angles. Therefore, the system can calculate what objects and thecoordinates of such objects entering the user's visual frame. If thesame coordinate system of the user is assigned to the real environ-ment viewed by the user (by pre-establishing transparent 3Dmodels of the environment “overlapping” the environmental im-ages and ascribing with the same coordinate system) that is, thesystem can identify the “visual target” of the user. Given this,“Line-of-Sight Positioning Interactive Interface” is expected to berealized if hand gestures are combined with visual images of theuser.

“Line-of-Sight Positioning Interactive Interface” is operated in ahighly intuitive manner. For instance, in Fig. 15, the system will auto-matically turn on the light by the central control system, when userwearing “Line-of-Sight Positioning Interactive Interface” watchesthe light bulb and followed by dragging the bulb to the “ON” blockon bottom left, after finger circling the image in mid-air. The sameapplies to other mechanical facilities too. A simple hand gesture canactivate the real facilities by linking to the central control system.

Possible realization of “Line-of-Sight Positioning Interactive Inter-face” depends on the realization of “Line-of-Sight Positioning” mecha-nism. Although still at its initial completion stage, the “Line-of-SightPositioning”mechanism and “AR image recording, replay, and leading”capabilities of HMTAR, may be further introduced into the develop-ment and application of “Line-of-Sight Positioning Interactive Inter-face.” Possible future applications in construction projects include:

(i) Instant 3D display of future construction progress;(ii) Flaws positioning for construction management;(iii) Making real-time additional or alternative design on site;(iv) Recording of AR images and replay or leading movement paths

for worker instruction and education purpose.

acy of various positioning applications.

e and relative accuracy of various positioning techniques [11].

Appendix B

The major codes of HMTAR related to Smooth and Bound design.

(continued on next page)

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Appendix B (continued)

114 C. Kuo et al. / Automation in Construction 33 (2013) 104–115

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