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The recent advances in the image data capture, storage and communication technologies have brought a rapid growth of image and video contents. Image and video data mining, the process of extracting hidden patterns from image and video data, becomes an important and emerging task. Despite a lot of previous work, data mining techniques that are successful in mining text and transaction data cannot simply apply to image and video data that are much more complex. Due to the structure and content variations of the visual patterns, it is not a trivial task to discover meaningful patterns in images and videos. This book presents a systematic study on mining common visual patterns in image and video data. Several novel data mining methods are developed for the discovery of different types of common visual patterns, including common object discovery, semantically meaningful visual pattern discovery, and recurring video pattern mining. The difficulties of the structure and content variations for mining complex visual patterns are addressed and efficient algorithms are proposed.
About the author
Dr. Junsong Yuan is a Nanyang assistant professor at Nanyang Technological University, Singapore. He received the Outstanding Ph.D. Thesis award from the EECS department in Northwestern University, USA, and was a recipient of the Doctoral Spotlight Award from IEEE Conf. Computer Vision and Pattern Recognition Conference (CVPR'09).
