For more information, please see www.ece.neu.edu/~yunfu/CfP/VECTaR2014.htm.
Call for Papers
The goal of this workshop is to provide a forum for recent research advances in the area of video event categorization, tagging and retrieval, particularly with the increasing BIG volume of video data. The workshop seeks original high-quality submissions from leading researchers and practitioners in academia as well as industry, dealing with theories, applications and databases of visual event recognition. Topics of interest include, but are not limited to:
- Big video event database gathering and annotation
- A large scale dataset benchmarking
- Deep learning for large scale event recognition
- Event detection in big social media
- Event recognition with depth cameras
- Multi-modal and multi-dimensional event recognition
- Multi-spectrum data fusion
- Spatial temporal features for event categorization
- Hierarchical event recognition
- Probabilistic graph models for event reasoning
- Global/local event descriptors
- Metadata construction for event recognition
- Event-based video segmentation and summarization
- Efficient indexing and concepts modeling for video event retrieval
- Semantic-based video event retrieval
- Online video event tagging
Aims and Scope
With the vast development of Internet capacity and speed, as well as wide adoptation of media technologies in people’s daily life, it is highly demanding to efficiently process or organize video events rapidly emerged from the Internet (e.g., YouTube), wider surveillance networks, mobile devices, smart cameras, depth cameras (e.g., kinect)etc. The human visual perception system could, without difficulty, interpret and recognize thousands of events in videos, despite high level of video object clutters, different types of scene context, variability of motion scales, appearance changes, occlusions and object interactions. For a computer vision system, it has been very challenging to achieve automatic video event understanding for decades. Broadly speaking, those challenges include robust detection of events under motion clutters, event interpretation under complex scenes, multi-level semantic event inference, putting events in context and multiple cameras, event inference from object interactions, etc.
In recent years, steady progress has been made towards better models for video event categorization and recognition, e.g., from modeling events with bag of spatial temporal features to discovering event context, from detecting events using a single camera to inferring events through a distributed camera network, and from low-level event feature extraction and description to high-level semantic event classification and recognition. However, the current progress in video event analysis is still far from its promise. It is still very difficult to retrieve or categorize a specific video segment based on their content in a real multimedia system or in surveillance applications. The existing techniques are usually tested on simplified scenarios, such as the KTH dataset, and real-life applications are much more challenging and require special attention. To advance the progress further, we must adapt recent or existing approaches to find new solutions for intelligent large scale video event understanding.
- Submission Deadline TBA, 2014
- Notification of Acceptance TBA, 2014
- Camera-Ready Submission TBA, 2014
- Workshop date TBA, 2014
- Prof. Thomas S. Huang, University of Illinois at Urbana-Champaign, USA
- Prof. Tieniu Tan, Chinese Academy of Sciences, China
- Dr. Yun Raymond Fu, Northeastern University, Boston, USA
- Dr. Ling Shao, The University of Sheffield, UK
- Dr. Jianguo Zhang, University of Dundee, UK
- Prof. Liang Wang, Chinese Academy of Sciences, China
- When submitting manuscripts to this workshop, the authors acknowledge that manuscripts substantially similar in content have NOT been submitted to another conference, workshop, or journal. However, dual submission to the ECCV 2014 main conference and VECTaR’14 is allowed.
- The format of a paper submission is the same as the ECCV main conference. Please follow instructions on the ECCV 2014 website http://eccv2014.org/author-instructions/.
- For the paper submission, please go to the Submission Website (https://cmt.research.microsoft.com/VECTAR2014/)
Each submission will be reviewed by at least three reviewers from program committee members and external reviewers for originality, significance, clarity, soundness, relevance and technical contents. Accepted papers will be published together with the proceedings of ECCV 2014.