X-Vision: Augmented Reality Revolutionized with Real time Sensing

Let's introduce X-Vision, an incredible tool based on Augmented Reality (AR) that takes visualization to the next level. It brings real-time sensing capabilities to a tagged environment, aiming to boost productivity and enhance user-environment interaction. X-Vision works wonders in a range of settings, including factories, smart spaces, homes, offices, maintenance/facility rooms, and operation theaters.

Abstract:

X-Vision revolves around an exceptional visualization tool based on Augmented Reality (AR) that operates in a tagged environment. This article presents the design and implementation of X-Vision, including the development of a physical prototype that can project mind-blowing 3D holograms. These holograms are encoded with real-time data, such as water level and temperature readings of common office/household objects. Additionally, the article delves into the quality metrics used to evaluate the performance of pose estimation algorithms, which play a crucial role in reconstructing 3D object data.

 

Introduction:

The realm of Augmented Reality (AR) has witnessed remarkable advancements driven by progress in computer vision, connectivity, and mobile computing. We now encounter various AR applications on a daily basis, such as Google Translate's augmented display, AR GPS navigation apps, and CityViewAR for tourism. These applications seamlessly bridge the physical and digital worlds by employing object identification or providing information about the physical space. Visual markers, 2D barcodes, and RFID tags serve as effective means to establish this connection. Among these options, RFID tags stand out with their unique advantages. They enable wireless communication within a short distance, eliminating the need for line of sight. Moreover, RFID tags are cost-effective and can be effortlessly attached to a wide range of inventory and consumer products. By harnessing the power of RFID technology, X-Vision wirelessly retrieves information about tagged object IDs and physical attributes, mapping them to a captivating digital avatar.

AR-Based Smart Environment:

AR technology seamlessly integrates digital components into our perception of the real world, enabling interactive bidirectional communication and control between users and objects across various domains. X-Vision falls into this exciting category by combining object recognition, 3D pose estimation, and RFID sensing capabilities to create a truly smart environment. Through the research and development of X-Vision, we aim to amplify user-environment interaction and elevate user experiences in areas such as education, tourism, and navigation.

Emerging RFID Applications:

RFID technology has gained significant traction in industries for identification and tracking purposes. Recent advancements have explored the fusion of RFID with computer vision and AR technologies, paving the way for X-Vision's breakthrough. X-Vision brings together these cutting-edge technologies for gaming, education, and mixed reality applications. By leveraging RFID tags for object identification and sensing, X-Vision unlocks the full potential of AR technology, creating immersive and interactive experiences that leave a lasting impact. Numerous studies have already showcased the effectiveness of AR and RFID tags in gaming, education, and information display. In this article, X-Vision not only utilizes RFID for object identification but also harnesses its power for wireless sensing of the environment and object attributes. This approach fosters a more intimate and comprehensive interaction between humans and the objects that surround them.

 

Object Identification and Pose Estimation:

To bring X-Vision to life, we employ an Intel RealSense D415 depth camera, capturing color and depth information. This camera is seamlessly integrated with a HoloLens device, enabling a powerful visual experience. The system utilizes advanced local feature-based object recognition algorithms to identify objects from a vast database. Once identified, the X-Vision system performs 3D pose estimation using the Iterative Closest Point (ICP) algorithm, aligning point clouds for accurate reconstruction. This dynamic combination of object identification and pose estimation empowers X-Vision to render augmented information with utmost precision.

 

RFID Sensing:

X-Vision operates within an office space equipped with state-of-the-art RFID infrastructure for conducting experiments. The system relies on Impinj Speedway Revolution RFID readers, expertly connected to circularly polarized Laird Antennas. We utilize Smartrac's paper RFID tags with Monza 5 IC, which serve as backscattered-signal-based water level sensors. In addition, we employ custom-designed tags equipped with EM 4325 IC to function as temperature sensors. To interface with RFID readers and collect tag data, we implement the Low Level Reader Protocol (LLRP) over the Sllurp Python library. We thoroughly evaluate the performance of the RFID sensing system, taking into account factors such as tag-reader separation and normalized RSSI scores. Through rigorous study, we establish the working ranges between the camera and target objects, as well as between tagged objects and readers. This ensures reliable visualization and top-notch sensing quality.

Conclusion:

Prepare to be amazed by X-Vision, an unparalleled augmented vision system that seamlessly overlays physical objects with 3D holograms. These holograms are encoded with valuable sensing information captured from tag sensors attached to everyday objects. In this article, we showcase the remarkable capabilities of X-Vision through two testing cases: water level sensing and temperature sensing. Additionally, we conduct experiments to evaluate the pose estimation pipeline and determine the working range of the system. The research and development of X-Vision offer immense promise in revolutionizing various domains and enhancing user experiences through the seamless integration of augmented reality, object recognition, and RFID sensing technologies.

 

Hashtag/Keyword/Labels:

#XVision #AugmentedReality #RFID #ObjectRecognition #PoseEstimation #SmartEnvironment

 

References/Resources:

1. Sun, Y., Kantareddy, S.N.R., Bhattacharyya, R., & Sarma, S.E. (2017). X-Vision: An Enhanced Augmented Reality Visualization Tool. Auto-ID Labs, MIT.

2. Agrawal, A., Anderson, G.J., Shi, M., & Chierichetti, R. (2018). Tangible play surface using passive RFID sensor array. CHI Conference on Human Factors in Computing Systems.

3. Ayala, A., Guerrero, G., Mateu, J., Casades, L., & Alam´an, X. (2015). Virtual touch flystick and primbox: Two case studies of mixed reality for teaching geometry. International Conference on Ubiquitous Computing and Ambient Intelligence.

 

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