chris williams npdlinfedacuk call papers special issue international journal computer vision probabilistic models image understanding aims scope probabilistic models provide compelling framework describing image video content levels ranging small image patches overall scene motion structure solicit papers describing development learning use principled probabilistic models image understanding relevant topics include limited low level models image patches random fields object recognition detection structural models image parsing structured models human motion probabilistic frameworks image representation efficient algorithms learning models frameworks datasets evaluating models particularly interested models incorporate rich structure deep graphical hierarchical compositional suited use within structurebased frameworks minimize amount labelled data required learning new classes exploiting latent structure reusing components priors consider submissions describing specific models position papers evaluation papers papers specific models either give enough detail moderately skilled graduate student reimplement exact model used reproduce experimental results provide full description open source implementation supplementary material must also include discussion competing approaches comparative testing establishes advantages limitations approach presented position papers clearly present arguments one generic approaches supporting indicative experimental results comparative tables thorough discussions existing literature evaluation papers describe benchmark challenge problem motivating discussing limitations existing models benchmarks debates regarding performance need resolved presenting detailed evaluation methodology dataset coverage collection labelling presenting representative sample benchmark results baseline methods recent methods literature benchmark dataset must nonproprietary publicly available authors test methods possible open source implementations baseline models feature sets also made available submissions papers following usual ijcv author guidelines submitted ijcv website choosing special issue article type probabilistic models image understanding regular journal articles 25 pages preferred short papers 10 pages wellbalanced surveys 30 pages also considered submissions subject peer review submissions returned without review feel well aligned goals special issue unsure whether intended submission scope send abstract draft editors special issue least one month submission deadline submission deadline july 21 2008 scheduled publication date summer 2009 guest editors bill triggs hnpgupoodiimagfr chris williams npdlinfedacuk fri 08 aug 2008 131009 0000 uai ijcv special issue probabilistic models image understanding