In computer vision, the bag-of-words (BoW) model has been widely applied to image related tasks, such as large scale image retrieval, image classification, and object categorization. The sparse coding...

Image fingerprints are perceptual features or short summaries of a given image. They can be used for identifying image contents just as human fingerprints are used for identification. In this paper, w...

Due to the huge intra-class variations for visual concept detection, it is necessary for concept learning to collect large scale training data to cover a wide variety of samples as much as possible. B...

Due to the existence of cross-domain incoherence resulting from the mismatch of data distributions, how to select sufficient positive training samples from scattered and diffused web resources is a ch...

Domain adaptive video concept detection and annotation has recently received significant attention, but in existing video adaptation processes, all the features are treated as one modality, while mult...

Cooking is a human activity with sophisticated process. Underlying the multitude of culinary recipes, there exist a set of fundamental and general cooking techniques, such as cutting, braising, slicin...

Content-based video indexing is a field of rising interest that has achieved significant progress in the recent years. However, it can be retrospectively observed that, while many powerful spatial des...

Community-based question answering systems have become very popular for providing answers to a wide variety of ”how-to” questions. However, most such systems present only textual answers. In many case...

Abstract Resampling detection is a helpful tool in multimedia forensics; however, it is a challenge task in cases with compression and noisy. In this paper, by modeling the recovery of edited images u...

Abstract In this paper, we present an efficient concept detection system based on a novel bag of words extraction method and sparse ensemble learning. The presented system can efficiently build the co...

A new framework for high-level feature extraction (or semantic concept detection) is proposed. In this system, features at different granularities are extracted, and four classifiers with complementar...

A great deal of region-related concept detection algorithms have been proposed so far, but there are few of them concerning about the problem of mismatched regions at training and testing stages. In o...