Title :
Study of Target Face Search Algorithm for Video Advertisement
Author :
Jihong Liu ; Yutao Fu ; Qi Zhang ; Yuting Geng
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
Retrieving the wanted contents within large amount of video quickly is one of the key technologies of advertisement recognition. This paper analyzed the principle of AdaBoost algorithm and SURF matching algorithm, and designed a system of target face retrieving. The Adaboost algorithm was used to detect the faces from video key flames, and SURF matching algorithm was used to match the targeted face in a video. This system especially solved the matching problem for the changed targeted face brought by the different angle of view and scale in the video. This work was programmed by C# language in the environment of Visual Studio 2010 and EmguCV. The experimental results showed that the system could retrieve the appearing time of the target face accurately, and it was easy to be operated and was with a certain robustness and practicability.
Keywords :
advertising; face recognition; image matching; learning (artificial intelligence); video retrieval; AdaBoost algorithm; C# language; EmguCV; SURF matching algorithm; Visual Studio; target face retrieval; target face search algorithm; targeted face matching; video advertisement recognition; video key flames; Classification algorithms; Educational institutions; Face; Face detection; Face recognition; Feature extraction; Streaming media; AdaBoost algorithm; SURF matching algorithm; face detection; face retrieval in video streaming;
Conference_Titel :
Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4799-7980-6
DOI :
10.1109/CSE.2014.304