目标分割与识别研究进展

Anshika Sharma, P. Singh, Palak Khurana
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引用次数: 11

摘要

本综述的主要目的是分析用于目标分割和识别的流行技术。本文对现有的各种目标分割和识别方法进行了系统的分析和介绍。目标分割的重要性在于识别视频中的目标。它主要用于视频监控系统,人体活动识别,包括静态和运动物体的阴影检测。物体识别在视频稳定、生物成像中的细胞计数和自动泊车系统中也有广泛的应用。谷歌的无人驾驶汽车和微软的Kinect系统也使用了物体识别方法来实现。我们总结了我们的发现,现有方法的各种优点和缺点,以及未来在这一领域研究的可能性。
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Analytical review on object segmentation and recognition
The prime objective of this review is to analyze popular techniques used for object segmentation and recognition. In this paper various existing object segmentation and recognition methodologies have been systematically analyzed and presented. The importance of object segmentation can be in identifying the object in a video. It is majorly used in video surveillance system, in human activity recognition, in shadow detection which includes both static and moving objects. The object recognition also has various applications in the field of video stabilization, cell counting in bio-imaging and in automated vehicle parking system. Google's driverless car and Microsoft's Kinect System also uses object recognition methodologies for its implementation. We have concluded our findings with the various pros and cons of the existing methods and with the possibility of future research in this area.
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