论文标题
检测，识别和跟踪：调查
Detection, Recognition, and Tracking: A Survey
论文作者
论文摘要
对于人类，对象检测，识别和跟踪是天生的。这些为人类在环境中感知其环境和物体的能力提供了能力。但是，这种功能在计算机中不能很好地转化。在计算机视觉和多媒体中，检测，识别和跟踪图像和/或视频中的对象变得越来越重要。这些应用中的许多应用程序，例如面部识别，监视，动画，用于跟踪功能和/或人。但是，这些任务证明了计算机有效地做到的挑战，因为有大量数据可以解析。因此，需要许多技术和算法，因此对尝试实现人类的感知进行了研究。在本文献综述中，我们专注于一些有关对象检测和识别的新技术，以及如何将跟踪算法应用于检测到的特征以跟踪对象的运动。
For humans, object detection, recognition, and tracking are innate. These provide the ability for human to perceive their environment and objects within their environment. This ability however doesn't translate well in computers. In Computer Vision and Multimedia, it is becoming increasingly more important to detect, recognize and track objects in images and/or videos. Many of these applications, such as facial recognition, surveillance, animation, are used for tracking features and/or people. However, these tasks prove challenging for computers to do effectively, as there is a significant amount of data to parse through. Therefore, many techniques and algorithms are needed and therefore researched to try to achieve human like perception. In this literature review, we focus on some novel techniques on object detection and recognition, and how to apply tracking algorithms to the detected features to track the objects' movements.
