CoMMA Combined Multi-Relational Multi-media Associations By Juveria Kanodia Muhammad Aurangzeb

Annotation of Images -Segmentation and Labeling -Low Level Features Red, Green, Blue, Yellow, Deg0, Deg45, Deg90, Deg135 -Lets try some annotation CoMMA

Multi Relational Association Rule Mining -Data in separate tables -IMAGETABLE has image features -KEYWORDTABLE had annotations -Try to get rules across the two tables -Decentralized Apriori, WARMR, Peano Trees

CoMMA Experiment Results Some rules that we got: 5Y -> SPARSE 5Y -> ISOLATED 48D45 -> WEEDS 48D45 -> BUSH 48D45 -> GRASS 4Y -> EARTH 4Y -> GRASS 4Y -> FLOWERS 4B -> POPPY 4B -> SMALL 4B -> DARK 339G -> DIRT 339G -> SHRUBS 370R -> FLOWERS 370R -> VINES

CoMMA Experiment Results Some annotated images: Auto Annotation RADIANT BUSH SMALL GRASS LEAVES FLOWERS BERRIES GROUND WEEDS EARTH DRY DESERT Original Keywords BUSH SMALL FLOWERS GROUND SMALL

CoMMA Auto Annotation DIRT NIGHT SKY SMALL EARTH GRASS LEAVES FLOWERS VINES BERRIES WEEDS RADIANT ISOLATED SHRUBS BUSH BRANCH GOTHIC PLANT TREES SPARSE BUG BRANCHES BUSHES Original Keywords FLOWERS VINES EARTH SMALL

CoMMA Auto Annotation: STILL LAKE SUMMIT ALASKA NEAR ROCK ROCKS DESERT MELTING WALLS ICE Original Keywords: LAKE SUMMIT IN ALASKA

CoMMA Auto Annotation: NIGHT TINY BUDS EARTH LEAVES FLOWERS LONG STAMEN DUSTY THIN BRANCH BRANCHES RADIANT SHRUBS BUSH SMALL GRASS DARK NUT STICKS NUTS ROCKS MIX MOUNDS BUNCH Original Keywords: TREES BUSHERS FERN

CoMMA Conclusion -Association rule mining good enough -Low level features reveal a lot of information -Any better ideas? -Sure there must be.. The search for the correct annotation goes on….