A hybrid method for object identification and event detection in video

P. KrishnaKumar, L. Parameswaran
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引用次数: 13

Abstract

Video event detection (VED) is a challenging task especially with a large variety of objects in the environment. Even though there exist numerous algorithms for event detection, most of them are unsuitable for a typical consumer purpose. A hybrid method for detecting and identifying the moving objects by their color and spatial information is presented in this paper. In tracking multiple moving objects, the system makes use of motion of changed regions. In this approach, first, the object detector will look for the existence of objects that have already been registered. Then the control is passed on to an event detector which will wait for an event to happen which can be object placement or object removal. The object detector becomes active only if any event is detected. Simple training procedure using a single color camera in HSV color space makes it a consumer application. The proposed model has proved to be robust in various indoor environments and different types of background scenes. The experimental results prove the feasibility of the proposed method.
视频中目标识别与事件检测的混合方法
视频事件检测(VED)是一项具有挑战性的任务,特别是在环境中对象种类繁多的情况下。尽管存在许多用于事件检测的算法,但其中大多数都不适合典型的消费者目的。提出了一种利用运动目标的颜色和空间信息对运动目标进行检测和识别的混合方法。在跟踪多个运动目标时,该系统利用了变化区域的运动。在这种方法中,首先,对象检测器将查找已经注册的对象的存在。然后将控件传递给事件检测器,该检测器将等待事件发生,该事件可以是对象放置或对象删除。只有在检测到任何事件时,对象检测器才会激活。简单的训练程序使用单一颜色的相机在HSV色彩空间,使其成为消费者的应用程序。该模型在各种室内环境和不同背景场景下均具有较强的鲁棒性。实验结果证明了该方法的可行性。
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