Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
International Journal of Computer Vision
The Semantic Pathfinder: Using an Authoring Metaphor for Generic Multimedia Indexing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Foundations and Trends in Information Retrieval
Audio-based semantic concept classification for consumer video
IEEE Transactions on Audio, Speech, and Language Processing
Can High-Level Concepts Fill the Semantic Gap in Video Retrieval? A Case Study With Broadcast News
IEEE Transactions on Multimedia
The ACM Multimedia Grand Challenge 2011 in a nutshell
ACM SIGMultimedia Records
Beyond audio and video retrieval: towards multimedia summarization
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
Short user-generated videos classification using accompanied audio categories
Proceedings of the 2012 ACM international workshop on Audio and multimedia methods for large-scale video analysis
Generating natural language summaries for multimedia
INLG '12 Proceedings of the Seventh International Natural Language Generation Conference
Multimedia event recounting with concept based representation
Proceedings of the 20th ACM international conference on Multimedia
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Automatically generating compact textual descriptions of complex video contents has wide applications. With the recent advancements in automatic audio-visual content recognition, in this paper we explore the technical feasibility of the challenging issue of precisely recounting video contents. Based on cutting-edge automatic recognition techniques, we start from classifying a variety of visual and audio concepts in video contents. According to the classification results, we apply simple rule-based methods to generate textual descriptions of video contents. Results are evaluated by conducting carefully designed user studies. We find that the state-of-the-art visual and audio concept classification, although far from perfect, is able to provide very useful clues indicating what is happening in the videos. Most users involved in the evaluation confirmed the informativeness of our machine-generated descriptions.