Title :
Video categorization using object of interest detection
Author :
Kowdle, Adarsh ; Chang, Kuo-Wei ; Chen, Tsuhan
Author_Institution :
Cornell Univ., Ithaca, NY, USA
Abstract :
Object of Interest (OOI) detection has been widely used in many recent works in video analysis, especially in video similarity and video retrieval. In this paper, we describe a generic video classification algorithm using object of interest detection. We use online user-submitted videos and aim to categorize the videos into six broad categories hot star, news, anime, pets, sports and commercials. We show through our experiments that, detecting and describing the object of interest improves the video classification accuracy by about 10 percentage points.
Keywords :
image classification; image segmentation; object detection; video signal processing; video analysis; video categorization; video classification; video retrieval; Accuracy; Hidden Markov models; Histograms; Internet; Nearest neighbor searches; Positron emission tomography; Visualization; Object of Interest detection; Video classification;
Conference_Titel :
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-7992-4
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2010.5652300
