Download Advances in Multimedia Modeling: 14th International by Yuli Gao, Jianping Fan, Hangzai Luo, Shin’ichi Satoh PDF

By Yuli Gao, Jianping Fan, Hangzai Luo, Shin’ichi Satoh (auth.), Shin’ichi Satoh, Frank Nack, Minoru Etoh (eds.)

Welcometothe14thInternationalMultimediaModelingConference(MMM2008), held January 9–11, 2008 at Kyoto collage, Kyoto, Japan. MMM is a number one overseas convention for researchersand practitioners to percentage their new rules, unique examine effects and sensible improvement stories from all multimedia similar components. It used to be a superb honor to have MMM2008, probably the most long-standing m- timedia meetings, at the most attractive and traditionally very important eastern towns. Kyoto used to be an historical capital of Japan, and was once and nonetheless is on the heartofJapanesecultureandhistory. Kyotoinwintermaydistinctivelyo?er the sober surroundings of an ink portray. you could take pleasure in outdated shrines and temples that are specified as international historical past websites. The convention venue was once the Clock Tower Centennial corridor in Kyoto college, that's one of many oldest universities in Japan. MMM2008 featured a entire software together with 3 keynote talks, six oral presentation classes, and poster and demo classes. The 133 s- missions incorporated a lot of top quality papers in multimedia content material research, multimedia sign processing and communications, and multimedia functions and prone. We thank our 137 Technical application Committee participants and reviewers who spent many hours reviewing papers and prov- ing helpful suggestions to the authors. in response to the three or four studies in step with paper this system Chairs made up our minds to simply accept basically 23 as oral papers and 24 as poster papers, the place each one kind of presentation might moreover current the paintings as a demo. The recognition expense of 36% follows the MMM culture of ful?lling fruitful discussions during the conference.

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Extra resources for Advances in Multimedia Modeling: 14th International Multimedia Modeling Conference, MMM 2008, Kyoto, Japan, January 9-11, 2008. Proceedings

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Figure 1 shows the main idea of the proposed algorithm. ” On the right, the three components of object function in MILC2 are explained. Experiments on TRECVID 2005 corpus show that the MILC2 algorithm performs better than the standard Support Vector Machine based approaches and the MLMI kernel method [5]. The rest of this paper is organized as follows. Section 2 gives the proposed algorithm, including the MLMI kernel and the MILC2 approach. Section 3 provides the implementation issues for solving MILC2 by CCCP.

Eventually, the concept 1 Multi-Layer Multi-Instance Learning with Inter-layer Consistency Constraint, M, I, L, C appeared twice, and pronounced as [milk skwE@]. 26 Z. Gu et al. Groundtruth yi Hyper-bag classification error Shot-layer prediction f (Ti1 ) Frame-layer prediction Inter-layer inconsistency Minimization measure max { f (Tim2 )} + - +++-++++ - +- -- +- f Region-layer prediction max { f (Tim3 ) } + - +++-++++ - +- -- +- - Classifier complexity f Fig. 1. MLMI setting in video concept detection and the proposed MILC2 algorithm.

Let f be a linear function in the mapped high dimensional space f (x) = W T φ(x) + b, where φ(·) is the mapping function. ,L 2 λl δlT 1 + δl∗T 1 min ∗ (9) l=2 ⎧ 1 − yi (W T φ(Ti ) + b) ≤ δ1i , i = 1, . . ,N 1 W φ(Tim ) ≤ δli , i = 1, . . , N 1 , l = 2, . . t. ,N 1 W T φ(Tim ) − W T φ(Ti ) ≤ δli∗ , i = 1, . . , N 1 , l = 2, . . , L; ⎪ ⎪ ⎩ ∗ i = 1, . . , N 1 , l = 2, . . (9) are non-linear concave-convex inequalities, and all the others are linear constraints; therefore, the constrained concave-convex procedure (CCCP) [10] is well suited to solve this optimization problem.

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