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Flexible Burst Image Capture System for Mobile Devices

机译:适用于移动设备的灵活的连拍图像捕获系统

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In this paper a newfangled selective image capturing approach is described where all events of the current scenario are intended to be captured. Mobile phone usage has seen an exponential increase in the last few years and hence mobile phone photography has progressed rapidly. Phone camera is your best camera, because it is always with you. Our photographic brains are switched on all the time, looking for possibilities to capture the expected and unexpected moments. There are numerous scenarios where a user might want to capture images without missing any event, which is tedious if manual clicking is adopted. To capture continuous shots burst mode is devised, but it has fixed rate of image capture and results in many similar and unnecessary images even if there is no significant change in the scenario. Towards such needs, it is quite necessary to develop an intelligent system that captures image only when a new information is added to the scenario, hence saving memory, enhancing battery life and thereby improving the overall device performance without restricting the user needs. A software based solution has been developed in this research that performs selective capture without human interaction by continuously varying rate of image capture by dissecting the scenario, identifying constituents and their characteristics, applying movement restrictions and identifying disruption parameters. In this way, it is ensured that all the useful information, which user wants from a scenario, is successfully captured. The proposed mechanism is called as Flexible Burst Image Capture System for Mobile Devices. It has three interdependent modules (1) Context Detection & Object Classification module (2) Object Tracking & Scene Change Detection module (3) Scene Change Estimation module. Content Detection and Object Classification module is responsible for identification of different objects/backgrounds entering and exiting the scene. Once the object/background is successfully identified, it classifies them further according to their type. Object Tracking and Scene Change Detection module monitors the identified objects/background by the first module. Scene Change Estimation module, takes continuous input from the first two modules to devise the new image capture rate so that only images representing some new and important information are captured, without any duplication. In this way this mechanism helps user to capture all important moments without compromising on storage space.
机译:本文介绍了一种新型的选择性图像捕获方法,其中打算捕获当前场景的所有事件。在最近几年中,手机的使用呈指数增长,因此手机摄影迅速发展。手机摄像头是您最好的摄像头,因为它永远伴随着您。我们的摄影大脑始终处于打开状态,寻找捕捉预期和意外时刻的可能性。在许多情况下,用户可能希望捕获图像而不丢失任何事件,如果采用手动单击,这将很繁琐。为了捕获连续镜头,设计了连拍模式,但是连拍模式具有固定的图像拍摄速率,即使场景没有明显变化,也可以生成许多相似且不必要的图像。针对这样的需求,非常有必要开发一种仅在向场景添加新信息时才捕获图像的智能系统,从而节省内存,延长电池寿命并因此改善整体设备性能而不限制用户需求。在这项研究中开发出了一种基于软件的解决方案,该解决方案通过剖析场景,确定成分及其特征,应用移动限制并确定破坏参数来不断改变图像捕获的速率,从而在没有人为干预的情况下执行选择性捕获。这样,可以确保成功捕获用户从场景中需要的所有有用信息。所提出的机制被称为用于移动设备的灵活突发图像捕获系统。它具有三个相互依存的模块(1)上下文检测和对象分类模块(2)对象跟踪和场景变化检测模块(3)场景变化估计模块。内容检测和对象分类模块负责识别进入和退出场景的不同对象/背景。成功识别对象/背景后,它将根据其类型进一步对其进行分类。对象跟踪和场景变化检测模块监视第一个模块识别的对象/背景。 “场景变化估计”模块从前两个模块获取连续的输入以设计新的图像捕获率,从而仅捕获表示某些新的重要信息的图像,而无需进行任何重复。这样,该机制可帮助用户捕捉所有重要时刻,而不会影响存储空间。

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