In the domain of video indexing, one of the research topics is the automatic extraction of information to reach the objective of automatically describing and organizing the content. Thinking of a video stream, different kinds of information can be taken into account, but we can suppose that most of the information is contained in the foreground objects so that number of objects, their shape, their contours and so on, can constitute a good guess for the content description. This paper describes a new approach to extract foreground objects in MPEG2 video stream, in the framework of "rough
indexing paradigm" we define. This paradigm leads us to reach the purpose in near real time, nevertheless maintaining a good level of details.
Interactivity is a main requirement for 3D visualization of
medical images in a variety of clinical applications. The good
matching between segmentation and rendering techniques allows
to design easy to use interactive systems which assist the physicians
in dynamically creating and manipulating 'diagnostically relevant'
images from volumetric data sets. In this work we consider the
above problem within an original interactive visualization
paradigm. By this paradigm we want to highlight the twofold
clinical requirement of a) detecting and visualizing structures of
diagnostic interest (SoDI's) and b) adding to the 3D scene some other
structures to create a meaningful visual context. Being the
opacity modulation of the different structures a crucial point,
we propose an opacity management which reflects the paradigm
ideas and operates by means of a twofold indexed look-up table (2iLUT). The 2iLUT consists of a combination of attribute based and object based opacity management and is here designed and tested in order to combine the time interaction benefits of an indexed opacity setting with the effective handling of the above classification and visualization clinical requirements.