چکیده :

Today, the number of available videos on the Internet is significantly increased. Content-based video retrieval is used for finding the users’ desired items among these big video data. Memorizing details of the videos and intricate relations between included objects in videos can be considered as the major challenges of this big data topic. A large portion of videodatarelatestothehumans.Thus,humanactionretrievalhasbeenintroducedasanewbig data topic that seeks to find video objects based on the included human action. Human action retrieval has been applicated in different domains such as video search, intelligent human– computer interaction, robotics, video surveillance and human behavior analysis. There are some challenges such as variations in rotation, scale, style and above-mentioned challenges for the big video data that can impress the retrieval accuracy. In this paper, a survey on human action retrieval studies is presented that the methodologies have been analyzed from action representation and retrieving perspectives. Moreover, limitations and common datasets of human action retrieval are introduced before describing the state-of-the-arts’ methodologies.

کلید واژگان :

Human action retrieval · Human action recognition · Big data · Action representation · Action search



ارزش ریالی : 600000 ریال
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