4,013 research outputs found

    Deep learning-based anomalous object detection system powered by microcontroller for PTZ cameras

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    Automatic video surveillance systems are usually designed to detect anomalous objects being present in a scene or behaving dangerously. In order to perform adequately, they must incorporate models able to achieve accurate pattern recognition in an image, and deep learning neural networks excel at this task. However, exhaustive scan of the full image results in multiple image blocks or windows to analyze, which could make the time performance of the system very poor when implemented on low cost devices. This paper presents a system which attempts to detect abnormal moving objects within an area covered by a PTZ camera while it is panning. The decision about the block of the image to analyze is based on a mixture distribution composed of two components: a uniform probability distribution, which represents a blind random selection, and a mixture of Gaussian probability distributions. Gaussian distributions represent windows in the image where anomalous objects were detected previously and contribute to generate the next window to analyze close to those windows of interest. The system is implemented on a Raspberry Pi microcontroller-based board, which enables the design and implementation of a low-cost monitoring system that is able to perform image processing.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

    Vision Sensors and Edge Detection

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    Vision Sensors and Edge Detection book reflects a selection of recent developments within the area of vision sensors and edge detection. There are two sections in this book. The first section presents vision sensors with applications to panoramic vision sensors, wireless vision sensors, and automated vision sensor inspection, and the second one shows image processing techniques, such as, image measurements, image transformations, filtering, and parallel computing

    An Empirical Evaluation of the Performance of Real-Time Illumination Approaches: Realistic Scenes in Augmented Reality

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    Augmented, Virtual, and Mixed Reality (AR/VR/MR) systems have been developed in general, with many of these applications having accomplished significant results, rendering a virtual object in the appropriate illumination model of the real environment is still under investigation. The entertainment industry has presented an astounding outcome in several media form, albeit the rendering process has mostly been done offline. The physical scene contains the illumination information which can be sampled and then used to render the virtual objects in real-time for realistic scene. In this paper, we evaluate the accuracy of our previous and current developed systems that provide real-time dynamic illumination for coherent interactive augmented reality based on the virtual object’s appearance in association with the real world and related criteria. The system achieves that through three simultaneous aspects. (1) The first is to estimate the incident light angle in the real environment using a live-feed 360∘ camera instrumented on an AR device. (2) The second is to simulate the reflected light using two routes: (a) global cube map construction and (b) local sampling. (3) The third is to define the shading properties for the virtual object to depict the correct lighting assets and suitable shadowing imitation. Finally, the performance efficiency is examined in both routes of the system to reduce the general cost. Also, The results are evaluated through shadow observation and user study

    Polarization-Based Illumination Detection for Coherent Augmented Reality Scene Rendering in Dynamic Environments

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    A virtual object that is integrated into the real world in a perceptually coherent manner using the physical illumination information in the current environment is still under development. Several researchers investigated the problem producing a high-quality result; however, pre-computation and offline availability of resources were the essential assumption upon which the system relied. In this paper, we propose a novel and robust approach to identifying the incident light in the scene using the polarization properties of the light wave and using this information to produce a visually coherent augmented reality within a dynamic environment. This approach is part of a complete system which has three simultaneous components that run in real-time: (i) the detection of the incident light angle, (ii) the estimation of the reflected light, and (iii) the creation of the shading properties which are required to provide any virtual object with the detected lighting, reflected shadows, and adequate materials. Finally, the system performance is analyzed where our approach has reduced the overall computational cost

    Design of Immersive Online Hotel Walkthrough System Using Image-Based (Concentric Mosaics) Rendering

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    Conventional hotel booking websites only represents their services in 2D photos to show their facilities. 2D photos are just static photos that cannot be move and rotate. Imagebased virtual walkthrough for the hospitality industry is a potential technology to attract more customers. In this project, a research will be carried out to create an Image-based rendering (IBR) virtual walkthrough and panoramic-based walkthrough by using only Macromedia Flash Professional 8, Photovista Panorama 3.0 and Reality Studio for the interaction of the images. The web-based of the image-based are using the Macromedia Dreamweaver Professional 8. The images will be displayed in Adobe Flash Player 8 or higher. In making image-based walkthrough, a concentric mosaic technique is used while image mosaicing technique is applied in panoramic-based walkthrough. A comparison of the both walkthrough is compared. The study is also focus on the comparison between number of pictures and smoothness of the walkthrough. There are advantages of using different techniques such as image-based walkthrough is a real time walkthrough since the user can walk around right, left, forward and backward whereas the panoramic-based cannot experience real time walkthrough because the user can only view 360 degrees from a fixed spot

    Photorealistic True-Dimensional Visualization of Remote Panoramic Views for VR Headsets

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    © 2023 IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/Virtual Reality headsets have evolved to include unprecedented display quality. Meantime, they have become light-weight, wireless and low-cost, which has opened to new applications and a much wider audience. Photo-based omnidirectional imaging has also developed, becoming directly exploitable for VR, with their combination proven suitable for: remote visits and realistic scene reconstruction, operator’s training and control panels, surveillance and e-tourism. There is however a limited amount of scientific work assessing VR experience and user’s performance in photo-based environment representations. This paper focuses on assessing the effect of photographic realism in VR when observing real places through a VR headset, for two different pixel-densities of the display, environment types and familiarity levels. Our comparison relies on the observation of static three-dimensional and omnidirectional photorealistic views of environments. The aim is to gain an insight about how photographic texture can affect perceived realness, sense of presence and provoked emotions, as well as perception of image-lighting and actual space dimension (true-dimension). Two user studies are conducted based on subjective rating and measurements given by users to a number of display and human factors. The display pixel-density affected the perceived image-lighting and prevailed over better lighting specs. The environment illumination and distance to objects generally played a stronger role than display. The environment affected the perceived image-lighting, spatial presence, depth impression and specific emotions. Distances to a set of objects were generally accurately estimated. Place familiarity enhanced perceived realism and presence. They confirmed some previous studies, but also introduced new elements.Peer reviewe
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