By Panagiotis Sidiropoulos, Vasileios Mezaris, Ioannis Kompatsiaris, Hugo Meinedo (auth.), Nicola Adami, Andrea Cavallaro, Riccardo Leonardi, Pierangelo Migliorati (eds.)
Covering probably the most state-of-the-art study at the supply and retrieval of interactive multimedia content material, this quantity of specifically selected contributions offers the main up-to-date standpoint on one of many preferred modern themes. the fabric represents prolonged models of papers awarded on the 11th overseas Workshop on snapshot research for Multimedia Interactive providers, an important overseas discussion board in this fast-moving field.
Logically geared up in discrete sections that procedure the topic from its numerous angles, the content material bargains in flip with content material research, movement and job research, high-level descriptors and video retrieval, 3-D and multi-view, and multimedia supply. The chapters conceal the best element of rising suggestions akin to using high-level audio info in enhancing scene segmentation and using subjective common sense for forensic visible surveillance. On content material supply, the publication examines either photographs and video, concentrating on key matters together with a good pre-fetching procedure for JPEG 2000 photograph sequences. extra contributions examine new methodologies for simultaneous block reconstruction and supply a trellis-based set of rules for quicker motion-vector determination making.
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Extra resources for Analysis, Retrieval and Delivery of Multimedia Content
According to the ground truth segmentation, all depicted shots belong to a single scene, related to field sprays in which shots of airplanes spraying interchange with farmers talking. g. the same person re-appearing, as is the case with the second of the two farmers shown above). AVSTG cannot fully remedy this over-segmentation, whereas MESTG manages to assign all 8 shots to the same scene, making use of the common airplane sound that is found in all shots in which a speaker is not included bined with the visual STG, using the merging approach of Sect.
Letters in fluorescent green would be discarded in the text candidate spotting phase due to low contrast if only luminance information had been used. 36 M. Leon et al. 5 Conclusions and Further Work We have presented a new technique for caption text detection. This technique will be included in a global indexing system and, therefore, works on a common hierarchical region-based image representation. The technique combines texture information (through Haar wavelet decomposition) and geometric information (through the analysis of the regions proposed by the hierarchical image model) to robustly extract caption text objects in the scene.
For this purpose, we used the groundtruth object masks provided with the database. We computed dense descriptors of 16 × 16 patches over a grid with spacing of 8 pixels, as proposed in . e. a subset of relevant object descriptors with their leveraging coefficients. Namely, we retained only examples with positive α j as prototypes for classifying test images. In Fig. 2 we show how values of prototype leveraging coefficients are distributed in each category. The best represented categories are those maximizing the integral of such 44 P.