We are delighted to welcome you, on behalf of the entire organizing committee, to the 3rd ACM International Conference on Multimedia Retrieval (ICMR 2013), held between April 16-19, 2013, in Dallas, Texas, USA.
ACM ICMR is the premier scientific conference for multimedia retrieval held worldwide, with the stated mission "to illuminate the state of the art in multimedia retrieval by bringing together researchers and practitioners in the field of multimedia retrieval". The conference aims to promote intellectual exchanges and interactions among scientists, engineers, students, multimedia researchers in academia as well as industry through various events, including keynote talk, oral, special, and poster sessions focused on research challenges and solutions, technical and industrial demonstrations of prototypes, tutorials, research and industrial panel.
In terms of numbers, we had around 96 valid submissions for the regular research papers of which 17 were accepted for oral presentation (17.7% acceptance rate) and 15 were accepted for poster presentation (giving an overall acceptance of 33 papers with 33.3% acceptance rate). We also have 5 research papers that were accepted as oral presentation papers for the special session on Social Events in Web Multimedia. We then have 15 technical demonstrations of systems showcasing key research contributions. Last, but not the least, the conference also has 2 state-of-the-art tutorials on advances in machine learning and similarity indexing for multimedia data.
One key new aspect of this 3rd ICMR is that we added a new event on doctoral symposium where we will have six research students presenting their dissertation research problems and get advice from leading multimedia retrieval researchers from all over the world. We believe this event would help us mentor future multimedia retrieval research leaders.
Retrieving geo-location of videos with a divide & conquer hierarchical multimodal approach
This paper presents a strategy to identify the geographic location of videos. First, it relies on a multi-modal cascade pipeline that exploits the available sources of information, namely the user's upload history, his social network and a visual-based ...
A unified framework for context assisted face clustering
Automatic face clustering, which aims to group faces referring to the same people together, is a key component for face tagging and image management. Standard face clustering approaches that are based on analyzing facial features can already achieve ...
Indexing and searching 100M images with map-reduce
Most researchers working on high-dimensional indexing agree on the following three trends: (i) the size of the multimedia collections to index are now reaching millions if not billions of items, (ii) the computers we use every day now come with multiple ...
Cited By
-
Zelensky A, Voronin V, Zhdanova M, Siryakov A, Egipko V, Urunov S, Semenishchev E and Dijk J (2022). Video segmentation on static and dynamic textures using a quaternion framework Artificial Intelligence and Machine Learning in Defense Applications IV, 10.1117/12.2641697, 9781510655553, (22)
- Preface Frontiers of Multimedia Research, (xi-xv)
- Wu Z, Yao T, Fu Y and Jiang Y Deep learning for video classification and captioning Frontiers of Multimedia Research, (3-29)
- Friedland G, Smaragdis P, McDermott J and Raj B Audition for multimedia computing Frontiers of Multimedia Research, (31-50)
- Alameda-Pineda X, Ricci E and Sebe N Multimodal analysis of free-standing conversational groups Frontiers of Multimedia Research, (51-74)
- Atrey P, Lathey A and Yakubu A Encrypted domain multimedia content analysis Frontiers of Multimedia Research, (75-104)
- Jeǵou H Efficient similarity search Frontiers of Multimedia Research, (105-134)
- Cui P Social-sensed multimedia computing Frontiers of Multimedia Research, (137-157)
- Singh V Situation recognition using multimodal data Frontiers of Multimedia Research, (159-189)
- Rizoiu M, Lee Y, Mishra S and Xie L Hawkes processes for events in social media Frontiers of Multimedia Research, (191-218)
- Ramanathan S, Gilani S and Sebe N Utilizing implicit user cues for multimedia analytics Frontiers of Multimedia Research, (219-251)
- Hsu C, Hong H, Elgamal T, Nahrstedt K and Venkatasubramanian N Multimedia fog computing Frontiers of Multimedia Research, (255-286)
- Chen K, Cai W, Shea R, Huang C, Liu J, Leung V and Hsu C Cloud gaming Frontiers of Multimedia Research, (287-314)