android智能手机上的实时视频处理和目标检测

S. Chaudhari, S. Patil
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引用次数: 2

摘要

随着智能手机变得越来越强大,它可以做更多以前需要电脑才能做的事情。对于利用智能手机的高处理能力的移动计算机视觉,一个设备捕捉的能力;过程;分析;对图像的理解。对于移动计算机视觉,智能手机必须更快、更实时。本研究在Android平台上使用OpenCV和核心库CamTest开发了两个应用程序,并实现了自己的算法。比较了两个Android应用程序的效率,发现OpenCV比CamTest执行得更快。在考虑效率的前提下,对最佳目标检测算法进行了研究,结果表明FAST算法具有速度和目标检测性能的最佳结合。接下来,投影目标识别系统采用FAST算法,其中利用支持向量机、bp神经网络对目标进行实时训练和验证。该应用程序完美地检测对象,使用SVM的识别时间约为2ms,使用BPNN的识别时间约为1ms。
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Real time video processing and object detection on android smartphone
As Smartphone is getting more potent, can do more superior stuffs that previous required a computer. For employing the high processing power of Smartphone is mobile computer vision, the ability for a device to capture; process; analyze; understanding of images. For mobile computer vision, Smartphone must be faster and real time. In this study two applications have been developed on Android platform using OpenCV and core library called as CamTest with own implemented algorithms. Efficiency of two Android applications have been compared and found that OpenCV performs faster than CamTest. The results of examining the best object detection algorithm with reverence to efficiency shows that FAST algorithm has the finest blend of speed and object detection performance. Next projected object recognition system using FAST algorithm, which uses SVM, BPNN for training and validation of object in real time. The application detects the object perfectly with recognition time around 2 ms using SVM and 1 ms using BPNN.
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