Relevant bibliographies by topics / Kinect

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Kinect'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "Kinect"

1

Wang, Yu, Fuxiang Chang, Yuanjie Wu, Ziran Hu, Lihui Li, Pengyu Li, Pu Lang, and Shouwen Yao. "Multi-Kinects fusion for full-body tracking in virtual reality-aided assembly simulation." International Journal of Distributed Sensor Networks 18, no. 5 (May 2022): 155013292210975. http://dx.doi.org/10.1177/15501329221097591.

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Skeleton tracking based on multiple Kinects data fusion has been proved to have better accuracy and robustness than single Kinect. However, previous works did not consider the inconsistency of tracking accuracy in the tracking field of Kinect and the self-occlusion of human body in assembly operation, which are of vital importance to the fusion performance of the multiple Kinects data in assembly task simulation. In this work, we developed a multi-Kinect fusion algorithm to achieve robust full-body tracking in virtual reality (VR)-aided assembly simulation. Two reliability functions are first applied to evaluate the tracking confidences reflecting the impacts of the position-related error and the self-occlusion error on the tracked skeletons. Then, the tracking skeletons from multiple Kinects are fused based on weighted arithmetic average and generalized covariance intersection. To evaluate the tracking confidence, the ellipsoidal surface fitting was used to model the tracking accuracy distribution of Kinect, and the relations between the user-Kinect crossing angles and the influences of the self-occlusion on the tracking of different parts of body were studied. On the basis, the two reliability functions were developed. We implemented a prototype system leveraging six Kinects and applied the distributed computing in the system to improve the computing efficiency. Experiment results showed that the proposed algorithm has superior fusion performance compared to the peer works.
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Nair, Arya J. "A Study on Different Recognition Systems based on Kinect Sensor." International Journal for Research in Applied Science and Engineering Technology 12, no. 1 (January 31, 2024): 731–35. http://dx.doi.org/10.22214/ijraset.2024.58038.

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Abstract: The Kinect is a motion-sensing gadget that lets us control a computer or gaming console without holding a controller. The influence of Kinect has spread well beyond the video game sector. The Kinect sensor is equipped with multiple innovative sensing modules. It is equipped with four microphones, an RBG camera, and a depth sensor to track body motion, recognize faces, and detect voices. The Kinect sensor's ability to offer depth and RGB-D visual data offers novel avenues in the field of artificial intelligence. The Kinect's adaptable capabilities in-depth perception, skeletal tracking, and voice input have been used for a wide range of interactive experiences, from gaming to healthcare, education, and more. To demonstrate the Kinect's versatility across several domains, the article explores how the technology has been incorporated into gesture recognition, facial recognition, gait, and even activity recognition.
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Mousavi Hondori, Hossein, and Maryam Khademi. "A Review on Technical and Clinical Impact of Microsoft Kinect on Physical Therapy and Rehabilitation." Journal of Medical Engineering 2014 (December 11, 2014): 1–16. http://dx.doi.org/10.1155/2014/846514.

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This paper reviews technical and clinical impact of the Microsoft Kinect in physical therapy and rehabilitation. It covers the studies on patients with neurological disorders including stroke, Parkinson’s, cerebral palsy, and MS as well as the elderly patients. Search results in Pubmed and Google scholar reveal increasing interest in using Kinect in medical application. Relevant papers are reviewed and divided into three groups: (1) papers which evaluated Kinect’s accuracy and reliability, (2) papers which used Kinect for a rehabilitation system and provided clinical evaluation involving patients, and (3) papers which proposed a Kinect-based system for rehabilitation but fell short of providing clinical validation. At last, to serve as technical comparison to help future rehabilitation design other sensors similar to Kinect are reviewed.
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Abdurrahman, Muhammad Rijal, Tatacipta Dirgantara, Sandro Mihradi, and Andi Isra Mahyuddin. "Validity of Kinect for Assessment of Joint Motion during Gait." Applied Mechanics and Materials 660 (October 2014): 921–26. http://dx.doi.org/10.4028/www.scientific.net/amm.660.921.

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One of the most common methods employed in gait analysis is the optical measurement method. While many analyzer systems are available commercially, the prices of those systems are rather prohibitive. In this work, an alternative method to obtain gait data using Microsoft KinectTM(Kinect) is investigated. Kinect, a 3D camera system created for gaming purposes, offers an ability which may be suitable for application in gait analysis. It has high mobility, needs no marker, is easy to use, and its price is relatively affordable. However, the performance of Kinect as a measurement tools in gait analysis must be first evaluated. In this work, Kinect is utilized to obtain joint movements of human walking motion to evaluate its suitability as an alternative motion analyzer in gait analyses. The data generated by Kinect are then processed to obtain gait parameters. The resulting parameters are compared to those obtained by 3D Motion Analyzer System that uses multi-camera previously developed. The results show promising prospect for Kinect application in gait analysis.
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Bilesan, Alireza, Shunsuke Komizunai, Teppei Tsujita, and Atsushi Konno. "Improved 3D Human Motion Capture Using Kinect Skeleton and Depth Sensor." Journal of Robotics and Mechatronics 33, no. 6 (December 20, 2021): 1408–22. http://dx.doi.org/10.20965/jrm.2021.p1408.

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Kinect has been utilized as a cost-effective, easy-to-use motion capture sensor using the Kinect skeleton algorithm. However, a limited number of landmarks and inaccuracies in tracking the landmarks’ positions restrict Kinect’s capability. In order to increase the accuracy of motion capturing using Kinect, joint use of the Kinect skeleton algorithm and Kinect-based marker tracking was applied to track the 3D coordinates of multiple landmarks on human. The motion’s kinematic parameters were calculated using the landmarks’ positions by applying the joint constraints and inverse kinematics techniques. The accuracy of the proposed method and OptiTrack (NaturalPoint, Inc., USA) was evaluated in capturing the joint angles of a humanoid (as ground truth) in a walking test. In order to evaluate the accuracy of the proposed method in capturing the kinematic parameters of a human, lower body joint angles of five healthy subjects were extracted using a Kinect, and the results were compared to Perception Neuron (Noitom Ltd., China) and OptiTrack data during ten gait trials. The absolute agreement and consistency between each optical system and the robot data in the robot test and between each motion capture system and OptiTrack data in the human gait test were determined using intraclass correlations coefficients (ICC3). The reproducibility between systems was evaluated using Lin’s concordance correlation coefficient (CCC). The correlation coefficients with 95% confidence intervals (95%CI) were interpreted substantial for both OptiTrack and proposed method (ICC > 0.75 and CCC > 0.95) in humanoid test. The results of the human gait experiments demonstrated the advantage of the proposed method (ICC > 0.75 and RMSE = 1.1460°) over the Kinect skeleton model (ICC < 0.4 and RMSE = 6.5843°).
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Venek, Verena, Wolfgang Kremser, and Thomas Stöggl. "Towards a Live Feedback Training System: Interchangeability of Orbbec Persee and Microsoft Kinect for Exercise Monitoring." Designs 5, no. 2 (April 15, 2021): 30. http://dx.doi.org/10.3390/designs5020030.

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Many existing motion sensing applications in research, entertainment and exercise monitoring are based on the Microsoft Kinect and its skeleton tracking functionality. With the Kinect’s development and production halted, researchers and system designers are in need of a suitable replacement. We investigated the interchangeability of the discontinued Kinect v2 and the all-in-one, image-based motion tracking system Orbbec Persee for the use in an exercise monitoring system prototype called ILSE. Nine functional training exercises were performed by six healthy subjects in front of both systems simultaneously. Comparing the systems’ internal tracking states from ’not tracked’ to ‘tracked’ showed that the Persee system is more confident during motion sequences, while the Kinect is more confident for hip and trunk joint positions. Assessing the skeleton tracking robustness, the Persee’s tracking of body segment lengths was more consistent. Furthermore, we used both skeleton datasets as input for the ILSE exercise monitoring including posture recognition and repetition-counting. Persee data from exercises with lateral movement and in uncovered full-body frontal view provided the same results as Kinect data. The Persee further preferred tracking of quasi-static lower limb motions and tight-fitting clothes. With these limitations in mind, we find that the Orbbec Persee is a suitable replacement for the Microsoft Kinect for motion sensing within the ILSE exercise monitoring system.
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Tran, Hoang Quang Minh, and Anh Vu Le. "Fusing Detected Humans in Multiple Perception Sensors Network." Journal of Advanced Engineering and Computation 1, no. 2 (November 30, 2017): 114. http://dx.doi.org/10.25073/jaec.201712.61.

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A fusion method is proposed to keep a correct number of humans from all humans detected by the robot operating system based perception sensor network (PSN) which includes multiple partially overlapped field of view (FOV) Kinects. To this end, the fusion rules are based on the parallel and orthogonal configurations of Kinects in PSN system. For the parallel configuration, the system will decide whether the detected humans staying in FOV of single Kinect or in overlapped FOV of multiple Kinects by evaluating the angles formed between their locations and Kinect original point on top view (x, z plane) of 3D coordination. Then, basing on the angles, the PSN system will keep the person stay in only one FOV or keep the one with biggest ROI if they stay in overlapped FOV of Kinects. In the case of Kinects with orthogonal configuration, 3D Euclidian distances between detected humans are used to determine the group of humans supported to be same human but detected by different Kinects. Then the system, keep the human with a bigger region of interest (ROI) among this group. The experimental results demonstrate the outperforming of the proposed method in various scenarios. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Badr, Ahmed Mangoud, Wael M. Mubarak Refai, Mohamed Gaber El-Shal, and Ahmed Nasef Abdelhameed. "Accuracy and Reliability of Kinect Motion Sensing Input Device’s 3D Models: A Comparison to Direct Anthropometry and 2D Photogrammetry." Open Access Macedonian Journal of Medical Sciences 9, no. D (May 14, 2021): 54–60. http://dx.doi.org/10.3889/oamjms.2021.6006.

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AIM: This study aims to evaluate the accuracy and reliability of Kinect motion sensing input device’s three-dimensional (3D) models by comparing it with direct anthropometry and digital 2D photogrammetry. MATERIALS AND METHODS: Six profiles and four frontal parameters were directly measured on the faces of 80 participants. The same measurements were repeated using two-dimensional (2D) photogrammetry and (3D) images obtained from Kinect device. Another observer made the same measurements for 30% of the images obtained with 3D technique, and interobserver reproducibility was evaluated for 3D images. Intraobserver reproducibility was evaluated. Statistical analysis was conducted using the paired samples t-test, interclass correlation coefficient, and Bland-Altman limits of agreement. RESULTS: The highest mean difference was 0.0084 mm between direct measurement and photogrammetry, 0.027 mm between direct measurement and 3D Kinect’s models, and 0.018 mm between photogrammetry and 3D Kinect’s. The lowest agreement value was 0.016 in the all parameter between the photogrammetry and 3D Kinect’s methods. Agreement between the two observers varied from 0.999 Sn-Me to 1 with the rest of linear measurements. CONCLUSION: Measurements done using 3D Images obtained from Kinect device indicate that it may be an accurate and reliable imaging method for use in orthodontics. It also provides an easy low-cost 3D imaging technique that has become increasingly popular in clinical settings, offering advantages for surgical planning and outcome evaluation.
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Altanis, Giannis, Michalis Boloudakis, Symeon Retalis, and Nikos Nikos Nikou. "Children with Motor Impairments Play a Kinect Learning Game: First Findings from a Pilot Case in an Authentic Classroom Environment." Interaction Design and Architecture(s), no. 19 (December 20, 2013): 91–104. http://dx.doi.org/10.55612/s-5002-019-007.

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This paper presents the first very positive findings from an empirical study about the effectiveness of the use of a Kinect learning game for children with gross motor skills problems and motor impairments. This game follows the principles of a newly presented approach, called Kinems, which advocates that special educators and therapists should use learning games that via embodied touchless interaction – thanks to the Microsoft Kinect camera- children with dyspraxia and other related disorders such as autism, Asperger’s Syndrome, and Attention Deficit Disorder, can improve related skills. Several Kinems games have been proposed (http://www.kinems.com). These games are innovative and are played with hand and body gestures. Kinems suggests that games should be highly configurable so that a teacher can modify the settings (e.g. difficult level, time settings, etc.) for the individual needs of each child. Also, a teacher should have access to kinetic and learning analytics of the child’s interaction progress and achievements should be safely stored and vividly presented.
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Caroff, Stanley N., Karen Yeomans, William R. Lenderking, Andrew J. Cutler, Caroline M. Tanner, Huda Shalhoub, Véronique Pagé, Jun Chen, Ericha Franey, and Chuck Yonan. "RE-KINECT." Journal of Clinical Psychopharmacology 40, no. 3 (2020): 259–68. http://dx.doi.org/10.1097/jcp.0000000000001201.

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Dissertations / Theses on the topic "Kinect"

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Manuylova, Ekaterina. "Investigations of stereo setup for Kinect." Thesis, Linköpings universitet, Institutionen för teknik och naturvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-75855.

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The main purpose of this work is to investigate the behavior of the recently released by Microsoft company the Kinect sensor, which contains the properties that go beyond ordinary cameras. Normally, in order to create a 3D reconstruction of the scene two cameras are required. Whereas, the Kinect device, due to the properties of the Infrared projector and sensor allows to create the same type of the reconstruction using only one device. However, the depth images, which are generated by the Infrared laser projector and monochrome sensor in Kinect can contain undefined values. Therefore, in addition to other investigations this project contains an idea how to improve the quality of the depth images. However, the base aim of this work is to perform a reconstruction of the scene based on the color images using pair of Kinects which will be compared with the results generated by using depth information from one Kinect. In addition, the report contains the information how to check that all the performed calculations were done correctly. All  the algorithms which were used in the project as well as the achieved results will be described and discussed in the separate chapters in the current report.
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Nordmark, Anton. "Kinect 3D Mapping." Thesis, Linköpings universitet, Datorseende, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-85158.

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This is a master thesis of the Master of Science degree program in Applied Physics and Electrical Engineering at Linköping University. The goal of this thesis is to find out how the Microsoft Kinect can be used as a part of a camera rig to create accurate 3D-models of an indoor environment. The Microsoft Kinect is marketed as a touch free game controller for the Microsoft Xbox 360 game console. The Kinect contains a color and a depth camera. The depth camera works by constantly projecting a near infrared dot pattern that is observed with a near infrared camera. In this thesis it is described how to model the near infrared projector pattern to enable external near infrared cameras to be used to improve the measurement precision. The depth data that the Kinect output have been studied to determine what types of errors it contains. The finding was that the Kinect uses an online calibration algorithm that changes the depth data.
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Eagle, James. "Kinect Surface Tracking." Thesis, University of Canterbury. Physics and Astronomy, 2014. http://hdl.handle.net/10092/10283.

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A cost effective method for evaluating patient motion during external beam radiotherapy has been developed. This system consists of a 3D depth camera and tracking software. The system was tested using a range of custom built phantoms and motion platforms. Kinect v1 and v2 sensors were chosen for this project due to their low cost and high resolution as compared to other depth cameras. Various tracking algorithms were evaluated to determine the optimal method for the system. Testing determined that the Kinect v2 was the more suitable sensor primarily due to the significantly lower depth variation of 0.6mm as compared to the Kinect v1 of 2.4mm. An analysis of tracking methods was performed and concluded that the least squares method provides the most accurate tracking in the clinical environment. This method is able to determine an object’s actual position accurate to 1.5mm 66% of the time.
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Kharchenko, N. I. "Technology of kinect." Thesis, Sumy State University, 2014. http://essuir.sumdu.edu.ua/handle/123456789/45412.

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Kinect (codenamed in development as Project Natal) is a line of motion sensing input devices by Microsoft. Based on a peripheral addition, it enables users to control and interact with their computer without the need for a game controller, through a natural user interface using gestures and spoken commands. The first-generation Kinect was first introduced in November 2010 in an attempt to broaden Xbox 360's audience.
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Dal, Monte Sara. "Kinect based personal trainer." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017.

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Hillman, Joel. "Kinect in retro games." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5201.

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Have you ever asked yourself whether new technology mixed with older might have a great outcome? How about using a modern kind of input control, such as a camera with gesture recognition in an older game? This study is meant to nd out whether or not camera-based input is suitable in older retro games and how it di ers in comparison to standard gamepad input. A modi ed version of In nite Super Mario is used to receive input from a Kinect application and control the character inside the game. Questionnaires and logging is added into the application to collect research data to help in answering the research questions. The evaluation consists of a pre-survey to collect background information about the player, empirical analysis of statistics collected during game play to measure performance and a post-survey to nd out the reactions of the subjects. T-tests are used to nd signi cant di erences in the test results and the participants are grouped based on their preference, former gamepad- and Kinect experience. The results indicate that players with lower gaming experience have a higher satisfaction using the Kinect as input method. Additionally gesture recognition appears to add an another fun factor to the game.
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Bengtsson, Morgan. "Indoor 3D Mapping using Kinect." Thesis, Linköpings universitet, Datorseende, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-106145.

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In recent years several depth cameras have emerged on the consumer market, creating many interesting possibilities forboth professional and recreational usage. One example of such a camera is the Microsoft Kinect sensor originally usedwith the Microsoft Xbox 360 game console. In this master thesis a system is presented that utilizes this device in order to create an as accurate as possible 3D reconstruction of an indoor environment. The major novelty of the presented system is the data structure based on signed distance fields and voxel octrees used to represent the observed environment.
Under de senaste åren har flera olika avståndskameror lanserats på konsumentmarkanden. Detta har skapat många intressanta applikationer både i professionella system samt för underhållningssyfte. Ett exempel på en sådan kamera är Microsoft Kinect som utvecklades för Microsofts spelkonsol Xbox 360. I detta examensarbete presenteras ett system som använder Kinect för att skapa en så exakt rekonstruktion i 3D av en innomhusmiljö som möjligt. Den främsta innovationen i systemet är en datastruktur baserad på signed distance fields (SDF) och octrees, vilket används för att representera den rekonstruerade miljön.
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Czompál, Zsolt. "Ovládání desktopu pomocí senzoru Kinect." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236428.

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The aim of this master's thesis was to create a user interface that allows controlling the PC using voice commands, static poses and dynamic gestures. It contains an implementation of a natural user interface that emulates the functionality of the keyboard and the mouse. In this thesis for detecting and tracking the user was used the sensor Kinect. For implementation I have chosen platform Windows and the Kinect for Windows SDK with programming language C#. During the implementation and testing of the interface, sensor Kinect for Xbox 360 was used. The result of this master's thesis is a natural user interface that allows controlling desktop applications without using keyboard or mouse, and that is comfortable and user-friendly.
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Brodd-Reijer, Christoffer. "Dance quantification with Kinect : Adjusting music volume by using depth data from a Kinect sensor." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-181928.

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Humans interact with computers in many various ways. Different interaction models are suited for different situations and tasks. This thesis explores the motion based interaction made possible by the Kinect for Windows device. A stand-alone library is built for interpreting, analyzing and quantifying movements in a room. It highlights the complexity in movement analysis in real time and discusses various algorithms for interpolation and filtering. The finished library is integrated into an existing music application by expanding its plugin system, allowing users to control the volume level of the playing music with the quantity of their body movements. The results are evaluated by subjective interviews with test subjects and objective measurements such as execution time and memory consumption. The results show that it is possible to properly quantify movement in real time with little memory consumption while still getting satisfying results, ending in a greater incentive to dance.
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Candefors, Joakim, and Mikael Söderqvist. "3D-ansiktsigenkänning med Kinect : En studie i ansiktsigenkänning med Kinect och dess beroende påansiktets horisontella rotation." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-157682.

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Denna rapport syftar till att utforska och visa på möjligheten till ansiktsigenkänning vilket görs lättillgängligt för allmänheten genom Microsoft Kinect for XBOX360 och eventuella framtida liknande lösningar med lågupplösta 3D-sensorer. Det finns många komplicerande faktorer inom ansiktsigenkänning och däribland ansiktsrotation. Beroendet på ansiktets horisontella vinklar i förhållande till Kinectenheten undersöks för 5 testsubjekt genom användandet av en 3D-baserad matchningsalgoritm.Detta sker med en metod baserad på Microsoft Kinect Face Tracking SDK och de ansiktsmodeller i 3D denna levererar. Undersökningens resultat är i linje med ansiktsigenkänningens problematik. Ett bättre resultat fås för sant positiva matchningar mellan frontala subjekt jämfört med horisontellt roterade ansikten. Undersökningen visar dock på att ansiktsigenkänning inte är helt underpresterande för de senare och att Kinect och Face Trackings SDK, utan större ingrepp, hanterar ansiktsigenkänning ganska bra.
This report aims to explore and show the possibilities of face recognition, which are made available to the public through Microsoft Kinect for XBOX 360 and future similar solutions with low resolution 3D sensors. There are many complicating factors in face recognition such as the rotation of the subjects face. The dependency of the face rotation in relation to the Kinect sensor is studied for 5 test subjects by using a 3D based matching algorithm. This is done with the Microsoft Kinect Face Tracking SDK and the 3D face models this SDK provides. The result of the study is in line with the complications with head rotation in facial recognition. For true positive matches frontal subjects gain better results compared with horizontally rotated subject faces. The study shows that the latter are not completely underperforming the frontal matches however, and that Kinect and Face Tracking SDK, without great interventions, handle face recognition rather well.
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Books on the topic "Kinect"

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Webb, Jarrett. Beginning Kinect Programming with the Microsoft Kinect SDK. Berkeley, CA: Apress, 2012.

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Webb, Jarrett, and James Ashley. Beginning Kinect Programming with the Microsoft Kinect SDK. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4105-8.

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Kramer, Jeff, Nicolas Burrus, Florian Echtler, Herrera C. Daniel, and Matt Parker. Hacking the Kinect. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-3868-3.

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Kean, Sean, Jonathan C. Hall, and Phoenix Perry. Meet the Kinect. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3889-8.

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Kramer, Jeff. Hacking the Kinect. Berkeley, CA: Apress, 2012.

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Pterneas, Vangos. Mastering the Microsoft Kinect. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-8070-6.

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Melgar, Enrique Ramos, Ciriaco Castro Díez, and Przemek Jaworski. Arduino and Kinect Projects. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4168-3.

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Davison, Andrew. Kinect open source programming secrets: Hacking the Kinect with OpenNI, NITE, and Java. New York: McGraw-Hill, 2012.

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Rahman, Mansib. Beginning Microsoft Kinect for Windows SDK 2.0. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2316-1.

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Dal Mutto, Carlo, Pietro Zanuttigh, and Guido M. Cortelazzo. Time-of-Flight Cameras and Microsoft Kinect™. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-3807-6.

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Book chapters on the topic "Kinect"

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Ramos, Enrique. "Kinect Basics." In Arduino and Kinect Projects, 23–34. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4168-3_2.

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Kramer, Jeff, Nicolas Burrus, Florian Echtler, Herrera C. Daniel, and Matt Parker. "Introducing the Kinect." In Hacking the Kinect, 1–9. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-3868-3_1.

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Kean, Sean, Jonathan C. Hall, and Phoenix Perry. "Scripting the Kinect." In Meet the Kinect, 63–83. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3889-8_4.

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Kean, Sean, Jonathan C. Hall, and Phoenix Perry. "Kinect for Creatives." In Meet the Kinect, 85–99. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3889-8_5.

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Kean, Sean, Jonathan C. Hall, and Phoenix Perry. "Microsoft’s Kinect SDK." In Meet the Kinect, 151–73. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3889-8_8.

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Kramer, Jeff, Nicolas Burrus, Florian Echtler, Herrera C. Daniel, and Matt Parker. "Multiple Kinects." In Hacking the Kinect, 207–46. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-3868-3_10.

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Kramer, Jeff, Nicolas Burrus, Florian Echtler, Herrera C. Daniel, and Matt Parker. "Hardware." In Hacking the Kinect, 11–39. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-3868-3_2.

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Kramer, Jeff, Nicolas Burrus, Florian Echtler, Herrera C. Daniel, and Matt Parker. "Software." In Hacking the Kinect, 41–63. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-3868-3_3.

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Kramer, Jeff, Nicolas Burrus, Florian Echtler, Herrera C. Daniel, and Matt Parker. "Computer Vision." In Hacking the Kinect, 65–87. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-3868-3_4.

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Kramer, Jeff, Nicolas Burrus, Florian Echtler, Herrera C. Daniel, and Matt Parker. "Gesture Recognition." In Hacking the Kinect, 89–101. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-3868-3_5.

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Conference papers on the topic "Kinect"

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Daphalapurkar, Chinmay P., Wenjuan Zhu, Ming C. Leu, Xiaoqing F. Liu, Alpha M. Chang, J. K. Gilpin-Mcminn, P. H. Wu, and S. D. Snodgrass. "Motion Capture for Human-Centered Simulation Using Kinects." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12645.

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Microsoft Kinect is capable of tracking human movements and can be used to develop various human-centered simulations. It is very attractive for certain applications because it is a low-cost, marker-less device. This paper presents our research toward characterizing the accuracy of Kinect and developing Kinect-based motion capture systems. Besides a single-Kinect system, a motion capture system with multiple Kinects were developed in order to increase the tracking volume and to improve the simulation fidelity. A motor-driven shutter mechanism was developed for use with each Kinect for the multi-Kinect system to address the issue of interference on the infrared light pattern without lowering the frame rate. The capabilities of the developed Kinect-based motion capture systems are demonstrated by tracking a human in performing a fastening operation on an aircraft fuselage mockup.
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Zhang, Mingshao, Zhou Zhang, Sven K. Esche, and Constantin Chassapis. "Algorithm Modification Approach to Improve the Kinect’s Performance in Point Cloud Processing." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-37064.

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Since its introduction in 2010, Microsoft’s Kinect input device for game consoles and computers has shown its great potential in a large number of applications, including game development, research and education. Many of these implementations are still in the prototype stages and exhibit a somewhat limited performance. These limitations are mainly caused by the quality of the point clouds generated by the Kinect, which include limited range, high dependency on surface properties, shadowing, low depth accuracy, etc. One of the Kinect’s most significant limitations is the low accuracy and high error associated with its point cloud. The severity of these defects varies with the points’ locations in the Kinect’s camera coordinate system. The available traditional algorithms for processing point clouds are based on the same assumption that input point clouds are perfect and have the same characteristics throughout the entire point cloud. In the first part of this paper, the Kinect’s point cloud properties (including resolution, depth accuracy, noise level and error) and their dependency on the point pixel location will be systematically studied. Second, the Kinect’s calibration, both by hardware and software approaches, will be explored and methods for improving the quality of its output point clouds will be identified. Then, modified algorithms adapted to the Kinect’s unique properties will be introduced. This method allows to better judge the output point cloud properties in a quantifiable manner and then to modify traditional computer vision algorithms by adjusting their assumptions regarding the input cloud properties to the actual parameters of the Kinect. Finally, the modified algorithms will be tested in a prototype application, which shows that the Kinect does have the potential for successful usage in educational applications if the according algorithms are design properly.
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Purwar, Anurag, and Rumit Desai. "Using Kinect to Capture Human Motion for Mechanism Synthesis, Motion Generation and Visualization." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-60499.

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In this paper, we are presenting a framework for capturing human motions using Microsoft Kinect sensor for the purpose of 1) generating task positions for mechanism and robot synthesis, and 2) generation and visualization of B-spline inter-polated and approximated motion from the captured task positions. The theoretical foundation of this work lies in Kinematic Mapping, Dual and Bi-quaternions, and NURBS (Non-Uniform Rational B-spline) geometry. Lately, Kinect has opened doors for creation of natural and intuitive human-machine interactive (HMI) systems in medicine, robotic manipulation, CAD, and many other fields, where visual-sensing and -capture is a central theme. Kinect has made a huge impact in physical therapy area, achieving new benchmarks in tele-rehabilitation by improving physical exercise assessment, monitoring and supervision using the skeletal data. Moreover, Kinect’s depth sensing capability has helped in retrieving depth information required for robotic vision in grasping, object recognition which was previously done using computationally demanding computer vision algorithms. Kinect’s point cloud data with interactive gestures has proven to be useful in various CAD software for conceptual design of shapes. Mechanism synthesis is one of the areas in Kinematics, where Kinect-provided skeletal data can be leveraged to design and develop highly customized end-user collaborated mechanism solutions. We demonstrate that using Kinect, OpenGL, and Openframeworks, we can capture discrete (or, key) rigid body displacements, continuous motions, and generate and visualize rational B-spline motions from captured key positions. Capturing only a few key positions results in significant data savings and also provides a natural way to create tasks for mechanism synthesis problems. The output is a set of dual quaternions and 4 × 4 homogeneous transforms representing a task motion, which can be used as an input for mechanism synthesis applications. The tool produced also allows users to generate trajectories of various points on a moving rigid body interactively. A Kinect-based capture of such motions can help create highly-customized assistive devices for people who suffer from a range of motion-related difficulties due to old age or disabilities.
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Shi, Yehua, Xiaoyi Wang, Cathy Lau, and Kai-Yu Tong. "Is it possible to use Kinect sensor for lying position rehabilitation exercise? Kinect V2 versus Azure Kinect." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003457.

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The availability of low-cost portable depth sensor camera brings opportunity to be applied in home-based rehabilitation exercise for stroke and other chronic disease patients. Kinect V2 seemed not feasible to easily track motion in a lying position, while the latest Microsoft Azure Kinect has improved the sensor. This paper experimentally explores the feasibility of Azure Kinect and Kinect V2 for lying position rehabilitation exercises and evaluate the tracking performance by changing the camera viewing angles. Two healthy subjects performed upper and lower limb rehabilitation exercise trial on the bed according to supine position and lateral position. The Kinect sensor was tested at 6 viewing angles in human body coronal plane and sagittal plane. Subject motion data and video were recorded and evaluated by two Kinect camera systems. The results showed that the hardware improvement such as resolution enhancement and the neural network motion tracking algorithm of the Azure Kinect depth camera led to higher performance in lying body motion recognition than Kinect v2 for most of the viewing angles. In conclusion, Azure Kinect could improve the lying position body tracking accuracy and it has great potential in the field of rehabilitation with lying position exercises.
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Martinez, Manuel, and Rainer Stiefelhagen. "Kinect unbiased." In 2014 IEEE International Conference on Image Processing (ICIP). IEEE, 2014. http://dx.doi.org/10.1109/icip.2014.7026171.

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Nebeling, Michael, David Ott, and Moira C. Norrie. "Kinect analysis." In EICS'15: ACM SIGCHI Symposium on Engineering Interactive Computing Systems. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2774225.2774846.

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McConchie, Jenny. "Kinect Sports." In ACM SIGGRAPH 2012 Computer Animation Festival. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2341836.2341871.

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Yang, Peicheng, Lei Xie, Chuyu Wang, and Sanglu Lu. "IMU-Kinect." In UbiComp '19: The 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3341162.3343766.

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Norman, Victor T. "Scratch + Xbox Kinect." In the 45th ACM technical symposium. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2538862.2539008.

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McEldowney, Scott C. "The Kinect Story." In Applied Industrial Optics: Spectroscopy, Imaging and Metrology. Washington, D.C.: OSA, 2012. http://dx.doi.org/10.1364/aio.2012.am3a.1.

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Reports on the topic "Kinect"

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Owens, Jason. Object Detection using the Kinect. Fort Belvoir, VA: Defense Technical Information Center, March 2012. http://dx.doi.org/10.21236/ada564736.

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Hamilton, Michael A., Patrick Mead, Rachael Lund, Jake Quartuccio, and Angela Nunnally. Detecting Key Inter-Joint Distances and Anthropometry Effects for Static Gesture Development using Microsoft Kinect. Fort Belvoir, VA: Defense Technical Information Center, September 2013. http://dx.doi.org/10.21236/ada595180.

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Marshak, Ronni. Kinek Package Delivery Service. Boston, MA: Patricia Seybold Group, January 2010. http://dx.doi.org/10.1571/pp01-14-10cc.

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Helsop, David. A comparison of two Turkish grinding stone assembleages: Kilise Tepe, Mut and Kinet Höyüt, Dörtyol. Edicions de la Universitat de Lleida, 2019. http://dx.doi.org/10.21001/rap.2019.extra-4.12.

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Lee, W. S., Victor Alchanatis, and Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7598158.bard.

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Original objectives and revisions – The original overall objective was to develop, test and validate a prototype yield mapping system for unit area to increase yield and profit for tree crops. Specific objectives were: (1) to develop a yield mapping system for a static situation, using hyperspectral and thermal imaging independently, (2) to integrate hyperspectral and thermal imaging for improved yield estimation by combining thermal images with hyperspectral images to improve fruit detection, and (3) to expand the system to a mobile platform for a stop-measure- and-go situation. There were no major revisions in the overall objective, however, several revisions were made on the specific objectives. The revised specific objectives were: (1) to develop a yield mapping system for a static situation, using color and thermal imaging independently, (2) to integrate color and thermal imaging for improved yield estimation by combining thermal images with color images to improve fruit detection, and (3) to expand the system to an autonomous mobile platform for a continuous-measure situation. Background, major conclusions, solutions and achievements -- Yield mapping is considered as an initial step for applying precision agriculture technologies. Although many yield mapping systems have been developed for agronomic crops, it remains a difficult task for mapping yield of tree crops. In this project, an autonomous immature fruit yield mapping system was developed. The system could detect and count the number of fruit at early growth stages of citrus fruit so that farmers could apply site-specific management based on the maps. There were two sub-systems, a navigation system and an imaging system. Robot Operating System (ROS) was the backbone for developing the navigation system using an unmanned ground vehicle (UGV). An inertial measurement unit (IMU), wheel encoders and a GPS were integrated using an extended Kalman filter to provide reliable and accurate localization information. A LiDAR was added to support simultaneous localization and mapping (SLAM) algorithms. The color camera on a Microsoft Kinect was used to detect citrus trees and a new machine vision algorithm was developed to enable autonomous navigations in the citrus grove. A multimodal imaging system, which consisted of two color cameras and a thermal camera, was carried by the vehicle for video acquisitions. A novel image registration method was developed for combining color and thermal images and matching fruit in both images which achieved pixel-level accuracy. A new Color- Thermal Combined Probability (CTCP) algorithm was created to effectively fuse information from the color and thermal images to classify potential image regions into fruit and non-fruit classes. Algorithms were also developed to integrate image registration, information fusion and fruit classification and detection into a single step for real-time processing. The imaging system achieved a precision rate of 95.5% and a recall rate of 90.4% on immature green citrus fruit detection which was a great improvement compared to previous studies. Implications – The development of the immature green fruit yield mapping system will help farmers make early decisions for planning operations and marketing so high yield and profit can be achieved.
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Bishnoi, P. R., R. B. Saeger, N. E. Kalogerakis, and J. Jeje. The kinetcs of formation & decomposition of hydrates from mixtures of natural gas components. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1986. http://dx.doi.org/10.4095/293492.

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Cuevas, Christian, Jennifer De Lurio, Andrew Furman, Randy Hulshizer, Marcus Lynch, and Brian Wilkinson. PCORI COVID-19 Scan: Anakinra (Kineret) and Self-Collection Test Kit (May 14-May 27, 2020). Patient-Centered Outcomes Research Institute (PCORI), June 2020. http://dx.doi.org/10.25302/bcs1.2020.6.

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Cerione, Richard A. Characterization of the Heregulin-Stimulated Activation of the Neu/ErB2 Tyrosine Kinese and Its Involvement in Breast Cancer. Fort Belvoir, VA: Defense Technical Information Center, August 1998. http://dx.doi.org/10.21236/ada366905.

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Vuksanović, Vuk, and Srđan Hercigonja. Između emocija i realizma: Dva lica turske spoljne politike na Balkanu. Belgrade Centre for Security Policy, June 2013. http://dx.doi.org/10.55042/dvvy2324.

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U poređenju sa komentarima o delovanju Rusije i Kine, prodornijem odnosu Turske prema Balkanu se ne poklanja dovoljno pažnje. Kako bi se ova praznina popunila, istraživački tim Beogradskog centra za bezbednosnu politiku (BCBP) sproveo je istraživanje zasnovano na analizi sekundarnog izvornog materijala ali, što je još važnije, i na razgovorima koji su sa šesnaest istraživača i pripadnika akademiske zajednice obavljeni u Istanbulu i Ankari. Iako konsultovani izvori imaju različite biografije i političke simpatije, istraživanjem je utvrđeno da su im određene teme svima zajedničke. Turska spoljna politika na Balkanu, naime, ima dva aspekta. Prvi je zasnovan na emocijama, i tu je spoljna politika države definisana njenim posebnim vezama sa tom oblašću, odnosno zajedničkom istorijom, društvenim vezama, faktorima identiteta i nasleđem Otomanskog carstva. S obzirom na društveno-kulturne veze i činjenicu da je Bosna i Hercegovina država u kojoj je to nasleđe najprisutnije, ona se u kontekstu posebnih veza sa Turskom pominje najčešće. Drugi pristup je ukorenjen u tradicionalnom spoljnopolitičkom realizmu koji proizlazi iz objektivne i proračunate procene regionalnog odnosa snaga i sopstvenih interesa. U okviru tog pristupa, Turska iz bezbednosnih i strateških razloga nastoji da deluje pragmatično i ostvaruje svoje namere na Balkanu, a da se pritom ne uplete u krize koje bi mogle da joj ometaju uticaj u regionu. Ovaj pristup Tursku vodi ka aktivnim odnosima sa Srbijom, koja je u strateškom smislu značajna zemlja u regionu, jer je Ankara duboko uverena da, ukoliko želi da bude delotvorna na Balkanu, mora da ima partnerski odnos sa Beogradom. Pri tome, mora da uspostavi ravnotežu između emocija i realizma. Mora pažljivo da neguje odnose sa zajednicama sa kojima ima kulturne i verske veze, kao što su Bošnjačke i Albanske, ali i da istovremeno pazi da od sebe ne odgurne države poput Srbije, čije joj je partnerstvo neophodno ukoliko želi da postigne uspeh na Balkanu. Turska spoljna politika u regionu prošla je kroz dve faze. U prvoj joj je politika prema Balkanu bila previše fokusirana na istoriju i faktore identiteta. Ta praksa je posebno došla do izražaja u fazi koju kritičari vole da nazivaju „neoosmanizmom“, a koja se najčešće povezuje sa Ahmetom Davutogluom, nekadašnjim ministrom inostranih poslova Turske (2009-2014) i kasnije premijerom (2014–2016). Treba naglasiti da je Redžep Tajip Ergodan i tada bio na vlasti, ali je za politiku prema Balkanu bio zadužen prvenstveno Davutoglu. Međutim, upravo zbog retorike kojom se akcenat stavljao na emocije, istoriju i kulturu, spoljna politika Ankare u regionu je tokom tog perioda doživljavala neuspehe jer su lokalni hrišćanski narodi Tursku doživljavali kao ekspanzionističku silu koja se poziva na ranije imperijalno nasleđe, i kao pristrasnog posrednika koji favorizuje muslimanske zajednice kakva je npr. bošnjačka. Realistički impulsi turske spoljne politike su na površinu izbili u drugoj fazi. Ona je započela odlaskom Ahmeta Davutoglua, kada je predsednik Redžep Tajip Erdogan preuzeo čvršću kontrolu nad spoljnom politikom zemlje, pa i prema Balkanu. Ankara od tada stavlja veći naglasak na realizam i pragmatizam, za razliku od ranijeg insistiranja na strastvenoj, istorijskoj retorici. Ovu transformaciju simbolizuju bliže veze sa Srbijom koje balkanskoj politici Ankare daju veću slobodu. Pre nego što se pojavila vest o Erdoganovoj pobedi, tokom predsedničkih i parlamentarnih izbora koji su u Turskoj održani u maju 2023. godine vodila se žestoka debata o budućem smeru spoljne politike zemlje. Dok su neki tvrdili da ona mora da ostane nepromenjena bez obzira na ishod izbora , drugi su verovali u potencijalne promene u sveukupnom odnosu zemlje sa akterima kao što su EU, SAD i Rusija . Međutim, ni pre ni nakon izbora nije bilo naznaka da će se spoljna politika Turske prema Balkanu bitno promeniti. Naprotiv, može da se očekuje da će upornost međunarodnih i domaćih faktora koji su u igri dovesti do dosledne balkanske politike Turske, te da će tamošnje spoljnopolitičke elite, kada se angažuju na Balkanu, i dalje biti prinuđene da balansiraju između emocija i realizma.
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