Smart Photos

Recent technological leaps have been a great catalyst for changing how people interact with the world around us. Specifically, the field of Augmented Reality has led to many software and hardware advances that have formed a digital intermediary between humans and their environment. As of now, Augmented Reality is available to the select few with the means of obtaining Google Glass, Oculus Rifts, and other relatively expensive platforms. Be that as it may, the tech industry\u27s current goal has been integration of this technology into the public\u27s smartphones and everyday devices. One inhibitor of this goal is the difficulty of finding an Augmented Reality application whose usage could satisfy an everyday need or attraction. Augmented reality presents our world in a unique perspective that can be found nowhere else in the natural world. However, visual impact is weak without substance or meaning. The best technology is invisible, and what makes a good product is its ability to fill a void in a person\u27s life. The most important researchers in this field are those who have been augmenting the tasks that most would consider mundane, such as overlaying nutritional information directly onto a meal [4]. In the same vein, we hope to incorporate Augmented Reality into everyday life by unlocking the full potential of a technology often believed to have already have reached its peak. The humble photograph, a classic invention and unwavering enhancement to the human experience, captures moments in space and time and compresses them into a single permanent state. These two-dimensional assortments of pixels give us a physical representation of the memories we form in specific periods of our lives. We believe this representation can be further enhanced in what we like to call a Smart Photo. The idea behind a Smart Photo is to unlock the full potential in the way that people can interact with photographs. This same notion is explored in the field of Virtual Reality with inventions such as 3D movies, which provide a special appeal that ordinary 2D films cannot. The 3D technology places the viewer inside the film\u27s environment. We intend to marry this seemingly mutually exclusive dichotomy by processing 2D photos alongside their 3D counterparts

Enabling Self-aware Smart Buildings by Augmented Reality

Conventional HVAC control systems are usually incognizant of the physical structures and materials of buildings. These systems merely follow pre-set HVAC control logic based on abstract building thermal response models, which are rough approximations to true physical models, ignoring dynamic spatial variations in built environments. To enable more accurate and responsive HVAC control, this paper introduces the notion of "self-aware" smart buildings, such that buildings are able to explicitly construct physical models of themselves (e.g., incorporating building structures and materials, and thermal flow dynamics). The question is how to enable self-aware buildings that automatically acquire dynamic knowledge of themselves. This paper presents a novel approach using "augmented reality". The extensive user-environment interactions in augmented reality not only can provide intuitive user interfaces for building systems, but also can capture the physical structures and possibly materials of buildings accurately to enable real-time building simulation and control. This paper presents a building system prototype incorporating augmented reality, and discusses its applications.Comment: This paper appears in ACM International Conference on Future Energy Systems (e-Energy), 201

GOTAN PROJECT: TANGO, A DANCE TO EXPERIENCE ONESELF

The tango brings out the true essence of the individuals, it removes every mask and stops the lies you tells yourself, forcingthe contact with yourself even before with the others. This is the essence on which we relied to propose a course of psychotherapy with basic elements of tango, as a peculiar mode of experiencing oneself. In this paper we analyze how Tango could become an interesting instrument for the cure and the prevention of psychological and physical problems

Game Implementation in Real-Time using the Project Tango

The goal of this senior project is to spread awareness of augmented reality, which Google defines as “a technology that superimposes a computer-generated image on a user\u27s view of the real world, thus providing a composite view.” It’s a topic that is rarely known to those outside of a technology related field or one that has vested interest in technology. Games can be ideal tools to help educate the public on any subject matter. The task is to create an augmented reality game using a “learn by doing” method. The game will introduce players to augmented reality, and thus demonstrate how this technology can be combined with the world around them. The Tango, Unity and Vuforia are the tools to be used for development. The game itself will be a coin collecting game that changes dynamically to the world around the player

Point Cloud Framework for Rendering 3D Models Using Google Tango

This project seeks to demonstrate the feasibility of point cloud meshing for capturing and modeling three dimensional objects on consumer smart phones and tablets. Traditional methods of capturing objects require hundreds of images, are very slow and consume a large amount of cellular data for the average consumer. Software developers need a starting point for capturing and meshing point clouds to create 3D models as hardware manufacturers provide the tools to capture point cloud data. The project uses Googles Tango computer vision library for Android to capture point clouds on devices with depth-sensing hardware. The point clouds are combined and meshed as models for use in 3D rendering projects. We expect our results to be embraced by the Android market because capturing point clouds is fast and does not carry a large data footprint

Localization from semantic observations via the matrix permanent

Most approaches to robot localization rely on low-level geometric features such as points, lines, and planes. In this paper, we use object recognition to obtain semantic information from the robot’s sensors and consider the task of localizing the robot within a prior map of landmarks, which are annotated with semantic labels. As object recognition algorithms miss detections and produce false alarms, correct data association between the detections and the landmarks on the map is central to the semantic localization problem. Instead of the traditional vector-based representation, we propose a sensor model, which encodes the semantic observations via random finite sets and enables a unified treatment of missed detections, false alarms, and data association. Our second contribution is to reduce the problem of computing the likelihood of a set-valued observation to the problem of computing a matrix permanent. It is this crucial transformation that allows us to solve the semantic localization problem with a polynomial-time approximation to the set-based Bayes filter. Finally, we address the active semantic localization problem, in which the observer’s trajectory is planned in order to improve the accuracy and efficiency of the localization process. The performance of our approach is demonstrated in simulation and in real environments using deformable-part-model-based object detectors. Robust global localization from semantic observations is demonstrated for a mobile robot, for the Project Tango phone, and on the KITTI visual odometry dataset. Comparisons are made with the traditional lidar-based geometric Monte Carlo localization

RIDI: Robust IMU Double Integration

This paper proposes a novel data-driven approach for inertial navigation, which learns to estimate trajectories of natural human motions just from an inertial measurement unit (IMU) in every smartphone. The key observation is that human motions are repetitive and consist of a few major modes (e.g., standing, walking, or turning). Our algorithm regresses a velocity vector from the history of linear accelerations and angular velocities, then corrects low-frequency bias in the linear accelerations, which are integrated twice to estimate positions. We have acquired training data with ground-truth motions across multiple human subjects and multiple phone placements (e.g., in a bag or a hand). The qualitatively and quantitatively evaluations have demonstrated that our algorithm has surprisingly shown comparable results to full Visual Inertial navigation. To our knowledge, this paper is the first to integrate sophisticated machine learning techniques with inertial navigation, potentially opening up a new line of research in the domain of data-driven inertial navigation. We will publicly share our code and data to facilitate further research

Development of modern methods for the diagnostics of murals in architectural monuments

The paper studies monitoring of the state of murals, retrieval of data pertaining to this state and management and storing of the said data. The possibility of integration of traditional methods of mural mapping and modern methods of data visualization, including new Google Project Tango device technology for fixation of complex textures of inner 3D volumes of architectural monuments has been investigated (for instance Assumption Cathedral). We further discuss the express-scanning of automated cartogramming for further comparison of states and methods of assessing the damage done to the mural. Results indicate that additional work is needed to improve the precision of the method.peer-reviewe