PlaNet - Photo Geolocation with Convolutional Neural Networks

Is it possible to build a system to determine the location where a photo was taken using just its pixels? In general, the problem seems exceptionally difficult: it is trivial to construct situations where no location can be inferred. Yet images often contain informative cues such as landmarks, weather patterns, vegetation, road markings, and architectural details, which in combination may allow one to determine an approximate location and occasionally an exact location. Websites such as GeoGuessr and View from your Window suggest that humans are relatively good at integrating these cues to geolocate images, especially en-masse. In computer vision, the photo geolocation problem is usually approached using image retrieval methods. In contrast, we pose the problem as one of classification by subdividing the surface of the earth into thousands of multi-scale geographic cells, and train a deep network using millions of geotagged images. While previous approaches only recognize landmarks or perform approximate matching using global image descriptors, our model is able to use and integrate multiple visible cues. We show that the resulting model, called PlaNet, outperforms previous approaches and even attains superhuman levels of accuracy in some cases. Moreover, we extend our model to photo albums by combining it with a long short-term memory (LSTM) architecture. By learning to exploit temporal coherence to geolocate uncertain photos, we demonstrate that this model achieves a 50% performance improvement over the single-image model

Adaptive Emotional Personality Model based on Fuzzy Logic Interpretation of Five Factor Theory

In recent years, emotional personality has found an important application in the field of human machine interaction. Interesting examples of this domain are computer games, interface agents, human-robot interaction, etc. However, few systems in this area include a model of personality, although it plays an important role in differentiating and determining the way they experience emotions and the way they behave. Personality simulation has always been a complex issue due to the complexity of the human personality itself, and the difficulty to model human psychology on electronic basis. Current efforts for emotion simulation are rather based on predefined set or inputs and its responses or on classical models which are simple approximate and have proven flaws. In this paper an emotional simulation system was presented. It utilizes the latest psychological theories to design a complex dynamic system that reacts to any environment, without being pre-programmed on sets of input. The design was relying on fuzzy logic to simulate human emotional reaction, thus increasing the accuracy by further emulating human brain and removing the pre-defined set of input and its matched output

Accuracy of 3D Point-Cloud and Photo-Based Models of City Street Intersections

From Georgia Southern University’s Built Environment and Modeling lab, this study compares point positions and distance measurements completed with state-of-the-art instruments and equipment. A modern, 12-second, laser scanner, a modern unmanned aerial vehicle and a highly accurate, 1-second robotic total station were employed for this study. The latter serving as the benchmark instrument. The main objective of this quantitative comparison is to explore the accuracy and usability of a relatively large point-cloud model, as a virtual surveying tool for redesign/reconstruction purposes. This project involves the generation of large, 3D, point-cloud models of two busy and complex city street intersections. One intersection encompasses an approximate area of 300 ft × 750 ft and containing five converging elements: three streets and two railroads. It is an accident-prone location requiring redesign. The second street intersection encompasses an approximate area of 1,500 ft × 2,500 ft, containing two streets intersecting at an approximate 45-degree angle. The resulting computer model has been geo-referenced in the Georgia East State Plane Coordinate System (SPCS) using control points with coordinates established by GPS (Global Positioning System) via a rapid, network-based, Real-Time Kinematic (RTK) approach. These city street intersections are within the Blue-Mile corridor in Statesboro, GA. Along with the Statesboro city engineering, the Blue-Mile corridor has plans to enhance and improve the traffic flow of the Blue-Mile corridor, which contains many businesses and restaurants. The final point-cloud models are to be donated to the city engineers to assist in the redesign of the intersections. A full analysis of the referred discrepancies is presented and recommendations on improving the overall current accuracies are provided

From Equilibrium to Steady-State Dynamics after Switch-On of Shear

A relation between equilibrium, steady-state, and waiting-time dependent dynamical two-time correlation functions in dense glass-forming liquids subject to homogeneous steady shear flow is discussed. The systems under study show pronounced shear thinning, i.e., a significant speedup in their steady-state slow relaxation as compared to equilibrium. An approximate relation that recovers the exact limit for small waiting times is derived following the integration through transients (ITT) approach for the nonequilibrium Smoluchowski dynamics, and is exemplified within a schematic model in the framework of the mode-coupling theory of the glass transition (MCT). Computer simulation results for the tagged-particle density correlation functions corresponding to wave vectors in the shear-gradient directions from both event-driven stochastic dynamics of a two-dimensional hard-disk system and from previously published Newtonian-dynamics simulations of a three-dimensional soft-sphere mixture are analyzed and compared with the predictions of the ITT-based approximation. Good qualitative and semi-quantitative agreement is found. Furthermore, for short waiting times, the theoretical description of the waiting time dependence shows excellent quantitative agreement to the simulations. This confirms the accuracy of the central approximation used earlier to derive fluctuation dissipation ratios (Phys. Rev. Lett. 102, 135701). For intermediate waiting times, the correlation functions decay faster at long times than the stationary ones. This behavior is predicted by our theory and observed in simulations.Comment: 16 pages, 12 figures, submitted to Phys Rev

Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs

The idea of computer vision as the Bayesian inverse problem to computer graphics has a long history and an appealing elegance, but it has proved difficult to directly implement. Instead, most vision tasks are approached via complex bottom-up processing pipelines. Here we show that it is possible to write short, simple probabilistic graphics programs that define flexible generative models and to automatically invert them to interpret real-world images. Generative probabilistic graphics programs consist of a stochastic scene generator, a renderer based on graphics software, a stochastic likelihood model linking the renderer's output and the data, and latent variables that adjust the fidelity of the renderer and the tolerance of the likelihood model. Representations and algorithms from computer graphics, originally designed to produce high-quality images, are instead used as the deterministic backbone for highly approximate and stochastic generative models. This formulation combines probabilistic programming, computer graphics, and approximate Bayesian computation, and depends only on general-purpose, automatic inference techniques. We describe two applications: reading sequences of degraded and adversarially obscured alphanumeric characters, and inferring 3D road models from vehicle-mounted camera images. Each of the probabilistic graphics programs we present relies on under 20 lines of probabilistic code, and supports accurate, approximately Bayesian inferences about ambiguous real-world images.Comment: The first two authors contributed equally to this wor