Advances in Multimedia Modeling: 14th International Multimedia Modeling Conference, MMM 2008, Kyoto, Japan, January 9-11, 2008, ProceedingsShin'ichi Satoh, Frank Nack, Minoru Etoh Springer, 2008. gada 22. janv. - 512 lappuses Welcometothe14thInternationalMultimediaModelingConference(MMM2008), held January 9–11, 2008 at Kyoto University, Kyoto, Japan. MMM is a leading international conference for researchersand industry practitioners to share their new ideas, original research results and practical development experiences from all multimedia related areas. It was a great honor to have MMM2008, one of the most long-standing m- timedia conferences, at one of the most beautiful and historically important Japanese cities. Kyoto was an ancient capital of Japan, and was and still is at the heartofJapanesecultureandhistory. Kyotoinwintermaydistinctivelyo?er the sober atmosphere of an ink painting. You can enjoy old shrines and temples which are designated as World Heritage Sites. The conference venue was the Clock Tower Centennial Hall in Kyoto University, which is one of the oldest universities in Japan. MMM2008 featured a comprehensive program including three keynote talks, six oral presentation sessions, and two poster and demo sessions. The 133 s- missions included a large number of high-quality papers in multimedia content analysis, multimedia signal processing and communications, and multimedia applications and services. We thank our 137 Technical Program Committee members and reviewers who spent many hours reviewing papers and prov- ing valuable feedback to the authors. Based on the 3 or 4 reviews per paper the Program Chairs decided to accept only 23 as oral papers and 24 as poster papers, where each type of presentation could in addition present the work as a demo. The acceptance rate of 36% follows the MMM tradition of ful?lling fruitful discussions throughout the conference. |
No grāmatas satura
1.–5. rezultāts no 54.
6. lappuse
... Component Analysis (KPCA) according to the selected basic image kernel [13]. The kernel PCA is obtained by solving the eigenvalue equation: Kv = λMv (5) where λ = [λ1 ,···,λ M] denotes the eigenvalues and v = [−→v1, ···, −→vM ] ...
... Component Analysis (KPCA) according to the selected basic image kernel [13]. The kernel PCA is obtained by solving the eigenvalue equation: Kv = λMv (5) where λ = [λ1 ,···,λ M] denotes the eigenvalues and v = [−→v1, ···, −→vM ] ...
9. lappuse
... component of the transformation is to be updated as: fi(xi) = ⎧ ⎨ ⎩ xi xi < ui a · (xi −ui) + ui x i ∈ [ui,vi ] x i + (a − 1)· (vi − ui) x i > vi (9) where vi > ui, a is a constant term that satisfies: a > 1 for expansion ...
... component of the transformation is to be updated as: fi(xi) = ⎧ ⎨ ⎩ xi xi < ui a · (xi −ui) + ui x i ∈ [ui,vi ] x i + (a − 1)· (vi − ui) x i > vi (9) where vi > ui, a is a constant term that satisfies: a > 1 for expansion ...
12. lappuse
... component analysis. Neural Computation 10(5), 1299–1319 (1998) 14. Vendrig, J., Worring, M., Smeulders, A.W.M.: Filter image browsing: Interactive image retrieval by using database overviews. Multimedia Tools and Applications 15, 83–103 ...
... component analysis. Neural Computation 10(5), 1299–1319 (1998) 14. Vendrig, J., Worring, M., Smeulders, A.W.M.: Filter image browsing: Interactive image retrieval by using database overviews. Multimedia Tools and Applications 15, 83–103 ...
14. lappuse
... component of an object). (SIFT) [8]. This part-based image representation allows for robustness against partial occlusions, clutter and varying object appearances caused by changes in pose, image capturing conditions, scale, translation ...
... component of an object). (SIFT) [8]. This part-based image representation allows for robustness against partial occlusions, clutter and varying object appearances caused by changes in pose, image capturing conditions, scale, translation ...
17. lappuse
... components of objects. Rather than in a conceptual manner, we define the 'semantic' of a visual 1 i = word probabilistically. Given object classes {}mi Cc = , the 'semantic' of a visual word w is defined as its contribution to the ...
... components of objects. Rather than in a conceptual manner, we define the 'semantic' of a visual 1 i = word probabilistically. Given object classes {}mi Cc = , the 'semantic' of a visual word w is defined as its contribution to the ...
Saturs
1 | |
13 | |
24 | |
35 | |
New Approach for Hierarchical Classifier Training and Multilevel Image Annotation | 45 |
Extracting Text Information for ContentBased Video Retrieval | 58 |
RealTime Video Surveillance Based on Combining Foreground Extraction and Human Detection | 70 |
Detecting and Clustering Multiple Takes of One Scene | 80 |
Blurred Image Detection and Classification | 277 |
CrossLingual Retrieval of Identical News Events by NearDuplicate Video Segment Detection | 287 |
Web Image Gathering with a PartBased Object Recognition Method | 297 |
A Query Language Combining Object Features and Semantic Events for Surveillance Video Retrieval | 307 |
Semantic Quantization of 3D Human Motion Capture Data Through SpatialTemporal Feature Extraction | 318 |
Fast Intermode Decision Via Statistical Learning for H264 Video Coding | 329 |
A Novel Motion Estimation Method Based on Normalized Cross Correlation for Video Compression | 338 |
Curved RayCasting for Displacement Mapping in the GPU | 348 |
An ImagesBased 3D Model Retrieval Approach | 90 |
Oh Web Image Where Art Thou? | 101 |
Complementary Variance Energy for Fingerprint Segmentation | 113 |
Similarity Search in Multimedia Time Series Data Using AmplitudeLevel Features | 123 |
Sound Source Localization with Noncalibrated Microphones | 134 |
Privacy Protected Video Surveillance System Using Adaptive Visual Abstraction | 144 |
DistributionBased Similarity for Multirepresented Multimedia Objects | 155 |
A Multimodal Input Device for Music Authoring for Children | 165 |
FreeShaped Video Collage | 175 |
AestheticsBased Automatic Home Video Skimming System | 186 |
Using Fuzzy Lists for Playlist Management | 198 |
Tagging Video Contents with PositiveNegative Interest Based on Users Facial Expression | 210 |
A MixedReality Game Based on Scene Identification | 220 |
RealTime Multiview Object Tracking in Mediated Environments | 230 |
Reconstruct 3D Human Motion from Monocular Video Using Motion Library | 242 |
Appropriate Segment Extraction from Shots Based on Temporal Patterns of Example Videos | 253 |
Fast Segmentation of H264AVC Bitstreams for OnDemand Video Summarization | 265 |
EmotionBased Music Visualization Using Photos | 358 |
Distant Collaboration Support System for Manufacturers | 369 |
Accurate Identifying Method of JPEG2000 Images for Digital Cinema | 380 |
Optimization of Spatial Error Concealment for H264 Featuring Low Complexity | 391 |
Temporal Error Concealment for H264 Using Optimum Regression Plane | 402 |
Transform Domain WynerZiv Codec Based on Turbo Trellis Codes Modulation | 413 |
Selective Sampling Based on Dynamic Certainty Propagation for Image Retrieval | 425 |
Local Radon Transform and Earth Movers Distances for ContentBased Image Retrieval | 436 |
Content Based Querying and Searching for 3D Human Motions | 446 |
Bimodal Conceptual Indexing for Medical Image Retrieval | 456 |
Audio Analysis for Multimedia Retrieval from a Ubiquitous Home | 466 |
Effectiveness of Signal Segmentation for Music Content Representation | 477 |
Probabilistic Estimation of a Novel Music Emotion Model | 487 |
Embedding High BitRate Data in Audio | 498 |
Author Index | 508 |
Citi izdevumi - Skatīt visu
Advances in Multimedia Modeling: 14th International Multimedia Modeling ... Shin'ichi Satoh,Frank Nack,Minoru Etoh Ierobežota priekšskatīšana - 2007 |
Bieži izmantoti vārdi un frāzes
AdaBoost algorithm analysis applied approach audio automatic average Berlin Heidelberg 2008 bitplane block blurred camera classifier clips clustering codec coding coefficients collage color color histogram component Computer Computer Vision content-based image retrieval corresponding database decoder defined denotes detection distance distribution emotion encoder error concealment estimation Etoh Eds evaluation feature extraction feature vectors feedback filtering frame function fuzzy lists Google Images Heidelberg histogram IEEE IEEE Trans image concepts image retrieval indexing input kernel keywords labeled learning LightCollabo LNCS macroblocks mapping matching microphones motion capture Multimedia object OFDM paper parameters partition performance pixels playlist Proc proposed method PSNR quantization query Radon Transform region relevant representation sampling scene Section selection semantic sequence shot signal similarity space spatial support vector machines synset techniques texture threshold tracking transform TRECVID users visual features visual synset visual words