Statistical modeling and conceptualization of natural images

Statistical Modeling and Conceptualization of Visual Patterns

Natural images contain an overwhelming number of visual patterns generated by diverse stochastic processes. Defining and modeling these patterns is of fundamental importance for generic vision tasks, such as perceptual organization, segmentation, and recognition.Theobjectiveof this epistemological paper is to summarize various threadsof research in the literature and to pursueaunified framework...

Statistics of Range Images

The statistics of range images from natural environments is a largely unexplored eld of research. It closely relates to the statistical modeling of the scene geometry in natural environments, and the modeling of optical natural images. We have use d a 3D laser rangender to collect range images from mixed forest scenes. The images are here analyzed with respect to di erent statistics.

Conceptualization of the dynamics and synergistic partnership between the agri-food production chain and public health veterinarians

Statistical Principles in Image Modeling

Images of natural scenes contain a rich variety of visual patterns. To learn and recognize these patterns from natural images, it is necessary to construct statistical models for these patterns. In this review article we describe three statistical principles for modeling image patterns: the sparse coding principle, the minimax entropy principle, and the meaningful alignment principle. We explai...

On Conceptualization as a Systematic Process

We are concerned with the early phases of ER-modeling consisting in the primary conceptualization of the underlying application domain. To this end we introduce a process model for the generation of a domain description. In virtue of its close relation with cognitive activity, this model enables the modeler as well as the user to comprehend the concepts of the resulting domain in a natural way.