Comparison of Natural Feature Descriptors for Rigid-Object Tracking for Real-Time Augmented Reality

2014 ◽  
Author(s):  
Francely Franco Bermudez ◽  
Christian Santana Diaz ◽  
Sheneeka Ward ◽  
Rafael Radkowski ◽  
Timothy Garrett ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Object Tracking ◽  
Real Time ◽  
Virtual Object ◽  
Interest Points ◽  
Rigid Object ◽  
Binary Descriptors ◽  
Rigid Objects ◽  
Natural Feature ◽  
Feature Descriptors

This paper presents a comparison of natural feature descriptors for rigid object tracking for augmented reality (AR) applications. AR relies on object tracking in order to identify a physical object and to superimpose virtual object on an object. Natural feature tracking (NFT) is one approach for computer vision-based object tracking. NFT utilizes interest points of a physcial object, represents them as descriptors, and matches the descriptors against reference descriptors in order to identify a phsical object to track. In this research, we investigate four different natural feature descriptors (SIFT, SURF, FREAK, ORB) and their capability to track rigid objects. Rigid objects need robust descriptors since they need to describe the objects in a 3D space. AR applications are also real-time application, thus, fast feature matching is mandatory. FREAK and ORB are binary descriptors, which promise a higher performance in comparison to SIFT and SURF. We deployed a test in which we match feature descriptors to artificial rigid objects. The results indicate that the SIFT descriptor is the most promising solution in our addressed domain, AR-based assembly training.

Real-Time Occlusion Between Real and Digital Objects in Augmented Reality

2018 ◽  
Author(s):  
Kevin Lesniak ◽  
Conrad S. Tucker
Keyword(s):  
Augmented Reality ◽  
Coordinate System ◽  
Real Time ◽  
Real World ◽  
Virtual Object ◽  
Virtual Objects ◽  
Common Coordinate System ◽  
Realistic Representation ◽  
Lead Users

The method presented in this work reduces the frequency of virtual objects incorrectly occluding real-world objects in Augmented Reality (AR) applications. Current AR rendering methods cannot properly represent occlusion between real and virtual objects because the objects are not represented in a common coordinate system. These occlusion errors can lead users to have an incorrect perception of the environment around them when using an AR application, namely not knowing a real-world object is present due to a virtual object incorrectly occluding it and incorrect perception of depth or distance by the user due to incorrect occlusions. The authors of this paper present a method that brings both real-world and virtual objects into a common coordinate system so that distant virtual objects do not obscure nearby real-world objects in an AR application. This method captures and processes RGB-D data in real-time, allowing the method to be used in a variety of environments and scenarios. A case study shows the effectiveness and usability of the proposed method to correctly occlude real-world and virtual objects and provide a more realistic representation of the combined real and virtual environments in an AR application. The results of the case study show that the proposed method can detect at least 20 real-world objects with potential to be incorrectly occluded while processing and fixing occlusion errors at least 5 times per second.

scholarly journals Implementasi Model Mobile Augmented Reality e-Booklet untuk Mempromosikan Object Wisata Unggulan Provinsi Riau dengan metode 3D Object Tracking

2016 ◽  
Vol 1 (2) ◽  
pp. 177
Author(s):  
Unang Rio ◽  
Susi Erlinda ◽  
Dwi Haryono
Keyword(s):  
Augmented Reality ◽  
Object Tracking ◽  
Real Time ◽  
Mobile Augmented Reality ◽  
Pass Filter ◽  
3D Object ◽  
High Pass Filter ◽  
High Pass

Intisari  - Provinsi Riau terletak di lokasi yang strategis dan memiliki kekayaan keindahan alam dan budaya  yang  unik,  Riau  menawarkan  banyak  tempat  wisata  baik alam dan  budaya.  Tujuan  dari penelitian ini untuk membuat aplikasi  yang membantu masyarakat  untuk mendapatkan informasi objek wisata unggulan di Provinsi Riau. Salah satu faktor yang menyebabkan kurang berkembangnya sektor pariwisata di Provinsi Riau saat ini adalah karena pengelolaan informasi yang bersifat promosi dan belum mampu memaksimalkan ketersediaan teknologi informasi yang tersedia. Penggunaan teknologi augmented reality adalah teknologi yang menggabungkan benda maya tiga dimensi ke dalam  sebuah  lingkungan  tiga-dimensi  nyata  dan  kemudian  memproyeksikan  benda-benda  maya secara real time. Markerless objek wisata unggulan adalah bono surfing, balap alur, tongkang bahan bakar, pantai Rupat, istana siak dan Candi Muara Takus. pembuatan obyek dan membaca penanda scan dari kamera menggunakan teknik markerbase dan Markerless dengan objek Pelacakan metode 3D dan algoritma SIFT (Skala Fitur invarian Transform). Proses yang terkandung dalam deteksi obyek membaca gambar, mempertajam gambar dengan memanfaatkan High Pass Filter; membaca gambar dari metode SIFT bahwa proses akan menghasilkan deteksi titik. Hasil pengujian untuk melihat efek dari jarak antara smartphone kamera dengan spidol, jarak yang diperoleh sangat ideal untuk menampilkan objek 3D, sampai 40 cm. pengujian aplikasi ARRiauTouris mampu mendeteksi penanda dengan jarak dekat 10 cm dan jarak maksimum 67 cm, dan memperoleh waktu rata-rata untuk objek (mean) antara 0,80 detik menjadi 0,93 detik. Kata kunci: obyek wisata, augmented reality, 3D pelacakan objek, provinsi riau

scholarly journals Real-Time Occlusion Handling in Augmented Reality Based on an Object Tracking Approach

Sensors ◽  
2010 ◽  
Vol 10 (4) ◽  
pp. 2885-2900 ◽  
Author(s):  
Yuan Tian ◽  
Tao Guan ◽  
Cheng Wang
Keyword(s):  
Augmented Reality ◽  
Object Tracking ◽  
Real Time ◽  
Occlusion Handling

Real-time semantics based plane object tracking for augmented reality

2020 ◽  
Author(s):  
Shaowu Peng ◽  
Ju Chen ◽  
Honggang Guan ◽  
Ruojing Huang ◽  
Shichao Ou
Keyword(s):  
Augmented Reality ◽  
Object Tracking ◽  
Real Time ◽  
Time Semantics

TrackingExpert: A Versatile Tracking Toolbox for Augmented Reality

2016 ◽  
Author(s):  
Rafael Radkowski ◽  
Timothy Garrett ◽  
Jarid Ingebrand ◽  
David Wehr
Keyword(s):  
Augmented Reality ◽  
Object Tracking ◽  
Pose Estimation ◽  
Software Package ◽  
Point Cloud ◽  
Promising Candidate ◽  
Rigid Object ◽  
Virtual Objects ◽  
Research Outcomes ◽  
Functional Areas

This paper presents a toolbox for rigid object tracking with a focus on augmented reality applications. Augmented reality relies on tracking to superimpose virtual objects on physical objects. Object tracking is usually based on registration and pose estimation techniques. Many different approaches have already been introduced. Our research focuses on tracking for application areas such as assembly assistance and the most promising candidate is rigid object tracking based on point cloud registration. Our work advances the robustness of point cloud-based tracking as well as the performance. One product of our research is our tracking tool TrackingExpert, which integrates all our research outcomes into one versatile software package. This paper introduces TrackingExpert covering functional areas such as the registration, visualizations, and experiment support. We also highlight several aspects which facilitate data analysis and ease our research.

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