3d visualization
With the recent breakthrough in technological advancement, this millennium brings us novel computer assisted techniques of 3D Visualization that can efficiently transform massive information into a highly ordered two & three dimensional visual forms. The development of computer aided tools in order to transcribe this large amount of abstract non numerical data to a compact and highly ordered visually presentable form involves the basic skills of Information Visualization.
The term Information Visualization was coined by the User Interface Research Group of Xerox PARC. They were the innovators of the core technological skill used to represent such unorganized abstract information in a visual form for an easy understanding, analysis and application of the data to predict the imminent interplays of a complicated process. The basic aim of all forms of Information Visualization is to organize the massive data into a highly ordered visual frame so that they can be scrutinized at a glance. The human mind being more efficient in the act of recognition rather than recall, can function with a better optimized memory in studying visual representations rather than analyzing abstract data.
The technique has found its application in all possible domains of analysis and research, from translating files and lines of codes in software, organizing vast bibliographic databases, to even representing complex networking processes and their interactions in an understandable visual format. Having such versatility, Information Visualization has outsourced into a number of technologically enriched domains, like, Data Visualization, Knowledge Visualization, Information Graphics, Scientific Visualization and Visual Design.
The 3D Visualization is immensely implemented in Scientific Visualization techniques and works in accordance to the fundamental aspects of Information Visualization. Similar to Information Visualization, the three dimensional visualization technique centers on the dynamics of visual representation and interactivity. Effective visualization techniques require efficient Multidimensional Scaling (MDS) that deals with pointing out the similarities and the discrepancies in the massive abstract data that is to be transcribed for the end user. Several computer generated programs have been developed for effective Multidimensional Scaling in order to facilitate Scientific Visualization. They work on the multidimensional algorithm starting with a matrix of item to item similarities in a massive data layout, eventually plotting them in a low dimensional space for effective 3D representation.
MDS is the platform that supports the fundamental pillars of 3D Visualization and can be broadly classified into three categories depending upon the nature of the input matrix used for tagging data items that are transcribed. They are:
1) Classical multidimensional scaling dealing with an input matrix pointing out discrepancies between pairs of items for generating an output matrix minimizing the strain loss during representation
2) Metric multidimensional scaling working efficiently to minimize a number of loss functions in the mapping processes using weighted input matrices of known distances. The technique of stress Majorization is often involved in such a scaling in order to relieve the stress function for better optimization
3) Non-metric multidimensional scaling involving both the item to item dissimilarities and their interspaced distances in the input matrix thereby increasing optimization by locating each and every item in a low dimensional space
Applying MDS, Scientific Visualization has been able to incorporate the three dimensional representation techniques that can effectively simulate real time processes creating digital virtual images for a candid representation of a complex network. Several scientific concepts that apparently seem to be highly abstract can easily be transcribed into more understandable virtual visual formats with proper dynamic inputs for analysis in real time. The complex data of the scientific instruments employed in geological, astrophysical and biomedical research can be easily represented in the form of three dimensional image maps and graphical layouts for an overall understanding and analysis of the represented information. The imaging techniques that are employed in Scientific Visualization involve the support of several computer aided tools for the proper analysis, interpretation and manipulation of scientific data. A host of supportive techniques have been employed in order to enhance 3D Visualization for monitoring complex abstract processes. Some of these widely implemented support systems involve:
1) Computer animation technology: The technology is used for creating virtual digital images involving both two dimensional and three dimensional computer graphics. Such techniques of Computer Generated Imagery are an aid to analyze and monitor the abstract scientific processes and their complex interplays in a virtual reality platform.
2) Computer simulation: The simulation technique is abundantly used in order to mimic certain abstract processes by transcribing the related data into dynamic visual models using computer programs. The dynamic representation used in computer simulation for understanding complex processes dealing with natural science, economics, psychology, physiological processes and even complicated networks and structural interplays in the World Wide Web.
3) Interface technology and perception: The concept of 3D scientific visualization has been enriched to a considerable extent with the interface technology and perception techniques that enables several computer generated programs to map the multidimensional model from the abstract data source of a dynamic interacting process. Interface technology and perception involves surface rendering, which is a widely accepted technique for generating programmed dynamic images from a multidimensional model. The images represent the geometry, texture and dynamics of the interaction from all possible viewpoints.
Computer animation, simulation techniques and surface rendering have been employed to understand the structure and function of certain bio-molecules and chemical interactions that are impossible to study in real set up and opened new gateways for medical research. The 3D Visualization has also been an effective tool to understand and analyze the abstract natural processes in physical and geological research. Human systems have been studied using simulated visualization tools to predict and interpret the ebbs and tides of socio-economic networks. The phenomenal breakthrough in visualization has even made it possible to analyze the large scale hypermedia structures like the World Wide Web.