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WO1993000651A1 - Methode permettant de representer visuellement une serie volumetrique de donnees multidimensionnelles non geometriques - Google Patents

Methode permettant de representer visuellement une serie volumetrique de donnees multidimensionnelles non geometriques Download PDF

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Publication number
WO1993000651A1
WO1993000651A1 PCT/US1992/005352 US9205352W WO9300651A1 WO 1993000651 A1 WO1993000651 A1 WO 1993000651A1 US 9205352 W US9205352 W US 9205352W WO 9300651 A1 WO9300651 A1 WO 9300651A1
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WIPO (PCT)
Prior art keywords
data set
data
voxels
variables
geometric
Prior art date
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Ceased
Application number
PCT/US1992/005352
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English (en)
Inventor
Jeffrey S. Saltzo
William Clifford
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Digital Equipment Corp
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Digital Equipment Corp
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Filing date
Publication date
Application filed by Digital Equipment Corp filed Critical Digital Equipment Corp
Publication of WO1993000651A1 publication Critical patent/WO1993000651A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G06T11/20—Drawing from basic elements, e.g. lines or circles
    • G06T11/206—Drawing of charts or graphs

Definitions

  • the visualization of 2-dimensional data in a 2-dimensional plane poses no technical difficulty. There are many ways to display such data including plotting points, drawing lines or curves, and using shading. The perception of the relation between such 2-dimensional data being represented is generally an easy task-for the viewer.
  • non-geometric multidimensional business data containing a plurality of independent variables does not lend itself naturally to 3-D graphical representation because there is no inherent spatial relationship among the multiple independent variables in the data base.
  • the graphical technique of scatter plotting represents one known method for visualizing non-geometric
  • the scatter plotting technique With the scatter plotting technique, a 3-dimensional frame or graph is used, with each coordinate of the data independently displayed as a dot or point. The observer of the scatter plot must exercise subjective judgment to infer patterns by visually perceiving the density of the dots or points within a specific region on the graph.
  • problems or difficulties arise with the scatter plotting technique due to the overlapping of coincident dots, the loss of depth perception and the inability to detect clustering or proximity of dots.
  • the ability of the scatter plot technique to convey relationships between portions or parameters of the data, for example, density information is limited.
  • the scatter plot technique does not provide the relationships between portions or
  • the present invention discloses a method of visually displaying a volumetric representation of nongeometric multidimensional data in a comprehensible fashion by quantizing the non-geometric data into 3-dimensional voxels of information.
  • a voxel is a 3-dimensional unit of volume containing one or more values associated with it.
  • the present invention utilizes a portion or subset of the data from a database containing a plurality of nongeometric multi-dimensional data records wherein each data record contains one or more variables of associated data.
  • This non-geometric multidimensional data set is transformed into a volumetric data set.
  • a volumetric data set is a three dimensional array of voxels. Quantification of the volumetric data set is achieved by partitioning each 3-dimensional axis with discrete incremental values.
  • the values of the voxels are determined by both the data records associated with each voxel and the operation performed on the data records.
  • quantization begins on two axes of a 3-dimensional space to form 2-dimensional square partitions.
  • the third dimension is then quantized to add a third dimension to the 2-dimensional squares to form a plane of voxels.
  • the data records are analyzed to determine which data records are associated with each voxel in the plane of voxels.
  • a volumetric data set is created which has a length of one in the third dimension.
  • the remaining voxels and their associated "values" in the 3-dimensional space are determined at each successive increment in the 3-dimensional space.
  • the newly created volumetric data set provides the information needed to display the data and relationships between portions of the data contained in the non-geometric multidimensional data set using known methods of
  • volumetric data set permits showing relationships among, at least 4 variables at one time.
  • additionally known techniques are available to further enhance the visual relationships between various portions of the data. DESCRIPTION OF THE DRAWINGS
  • FIG. 1 is a flow chart implementing the present invention.
  • FIG. 2 shows a volumetric representation of data relationships between the selected variables age, salary and seniority according to the present invention.
  • FIG. 3 shows a known 3-D scatter plot technique of illustrating data relationships between the same data illustrated in FIG. 2.
  • FIG. 4 shows a shrink wrapping of the volumetric representation of FIG. 3 around all voxels with at least fifty people.
  • FIG. 5 shows apparatus for implementing the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
  • FIG. 1 shows a flow chart of the method steps of the present invention
  • FIG. 5 shows apparatus for implementing the present invention.
  • step 10 multidimensional data from a non-geometric data base 110 contained on an auxiliary disk storage unit 108 is used as input.
  • the data set is
  • the user After the data set is read into main memory 106, at step 12, the user, through a keyboard 100 attached to the Terminal 102, or other suitable input device, selects three variables from the plurality of variables of the
  • non-geometric multidimensional data set to identify the x, y, and z axes in the three-dimensional space.
  • the three variables can be any three variables within the set of non-geometric multidimensional data. The user chooses the three variables depending upon the nature of the
  • the desired quantification for each axis is set at step 14.
  • the user through the use of the keyboard 100, assigns three incremental values to partition each x, y and z axis.
  • a user could define the quantification of the x axis to be on a per-year basis, the quantification of y to be per $1,000, and the
  • quantification of the x axis could be 50% of the sales commission goal for the first incremental value and 10% of the sales commission goal for subsequent incremental values
  • the quantification of the y axis could be by months of the year
  • the quantification of the z axis could be brown, blue, hazel, green, and other.
  • the quantification of the x, y and z axis establishes the height, width, and length of each voxel in units of the chosen x, y and z increments. Thus, the volume that each voxel occupies in the quantized three-dimensional space is defined.
  • all records in the data set are analyzed by CPU 104 to identify which records are associated with each voxel.
  • Data records contained within a given voxel and data records within neighboring voxels can be associated with the given voxel.
  • a weighted average of the data records contained within voxels neighboring a selected voxel can be used to determine the value of said selected voxel.
  • Neighboring means the defined relationship between voxels such as adjacent voxels or voxels no more than two removed from the subject voxel or any other defined relationship. Such a technique can be used to smooth or accentuate all areas where surrounding voxels have abrupt changes in values.
  • a distribution function is then selected by the user through the keyboard 100 at step 18 to map the identified data records for each voxel to one or more values for that voxel.
  • the distribution function in mapping to the value or values for a voxel can consider either the data within the voxel or the data associated with the voxel.
  • the choice of distribution functions implementing the present invention depends entirely upon the database information and the relationships between the portions of the data the user wishes to view. Examples include averaging last year's pay raises, counting the number of employees, and determining the median number of dependents of all
  • the distribution function has the capability of operating on more than one variable in the data set.
  • the distribution function could, for each
  • the data is also
  • the user through use of a keyboard 100 selects if filtering is required. If filtering is chosen by the user, the user enters the type of filtering through use of the keyboard 100 at step 22 and the
  • Filtering provides the ability to isolate selected data records in the database.
  • the preferred embodiment has the capability to take a "time-slice" of the volumetric data set at any given point in time. This is achieved by the user, through use of a keyboard 100, selecting the filtering option at Step 20 and assigning a specific filtering time frame at Step 22. Then, the CPU 104 filters out all data records outside of the chosen time frame at Step 24.
  • the distribution function is implemented by the CPU 104 to determine the values of each voxel.
  • the distribution function maps the data records associated with each voxel to one or more values for each voxel. With one or more values associated to each voxel, a volumetric data set is created and represented by a 3-dimensional array containing one or more values for each voxel.
  • volumetric data set is then stored on the auxiliary disk storage 108 at step 28.
  • a computer program written in the C-programming language capable of performing the steps 10 through 28 of the present invention is the preferred embodiment and is set forth in Table A.
  • the program uses a non-geometric multidimensional data set and user input to generate a file containing a volumetric representation of the non-geometric multidimensional data.
  • x_axis atoi ( argv[i+l] );
  • y_axis atoi ( argv[i+l] );
  • bucket_val atoi ( argv[i+l] ); i++; argc ⁇ ;
  • fp_out fopen( filename_out, "w");
  • bucket_count (int *)malloc( size );
  • bucket_vol (int *)malloc( size );
  • bucket_vol[i] 0;
  • VOLUME_ELEMENT (list[x_axis ] ,list[y_axis],list ⁇ z_axis]);
  • bucket_vol [ vol_index ] + list [ bucket_val
  • temp[0] (unsigned char) info
  • printf(" can not write to output file ⁇ n" );
  • the data is graphically displayed in three dimensions on the terminal 102.
  • a graphical visualization tool like AVS is used.
  • AVS a sphere is displayed at each of the voxels on the terminal 102.
  • the radii of the spheres are proportional to the values of each voxel.
  • the voxel with the largest value has the largest sphere associated with it.
  • the spheres are proportionally smaller in voxels which have proportionally smaller values.
  • FIG. 2 An illustration of the graphic visualization generated by the present invention is set forth in FIG. 2.
  • the employee database of the above example is used as input.
  • the x, y and z variables are chosen as age, salary and seniority.
  • the value of the voxel ⁇ and the associated radius of the sphere within each voxel ⁇ is determined by counting the number of employees within the given voxel. In this example, no filtering is performed. From FIG. 2, an expected trend is visually illustrated:
  • FIG. 2 also shows that very recently a large number of older, well paid, and more senior people have been hired.
  • FIG. 3 shows the results of the same data used to generate FIG. 2 displayed using the scatter plot technique. As can be seen in FIG. 3, the scatter plot technique is unable to convey the above mentioned trends in employee salary.
  • FIG. 3 shows a cluster of salaries ranging from about 60 to 70; however, the age and seniority of the people in the cluster cannot be determined from FIG. 3.
  • the graphical technique commonly known as isosurfacing or shrink wrapping represents a method for visualizing multidimensional volumetric data in a 3-dimensional space.
  • the shrink wrapping technique With the shrink wrapping technique, coordinates which contain the same selected values are graphically displayed and shaded together.
  • FIG. 4 shows the volumetric data generated by the present invention in FIG. 2 shrink wrapped around all voxels with at least fifty people. Without the volumetric data generated by the present invention, the application of the shrink wrap technique is not possible.
  • the shrink wrap technique requires a volumetric data set and cannot show
  • invention describes a method for visualizing a volumetric representation of non-geometric multidimensional data by quantizing selected variables of the non-geometric

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

L'invention concerne une méthode de transformation de données non géométriques en représentation volumétrique. Les données non géométriques sont difficiles à représenter en trois dimensions car il n'existe généralement pas de rapports spatiaux inhérents entre les données. L'invention permet de présenter les données sous forme volumétrique et de les afficher au moyen de techniques de visualisation connues. La présentation sous forme volumétrique permet à l'observateur de percevoir plus facilement les rapports entre les données.
PCT/US1992/005352 1991-06-28 1992-06-25 Methode permettant de representer visuellement une serie volumetrique de donnees multidimensionnelles non geometriques Ceased WO1993000651A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US72453491A 1991-06-28 1991-06-28
US724,534 1991-06-28

Publications (1)

Publication Number Publication Date
WO1993000651A1 true WO1993000651A1 (fr) 1993-01-07

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PCT/US1992/005352 Ceased WO1993000651A1 (fr) 1991-06-28 1992-06-25 Methode permettant de representer visuellement une serie volumetrique de donnees multidimensionnelles non geometriques

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2001003053A1 (fr) * 1999-06-30 2001-01-11 Bayes Information Technology Ltd. Procede et systeme de visualisation
EP3460646A4 (fr) * 2016-05-19 2019-04-24 Sony Corporation Dispositif de traitement d'informations, programme et système de traitement d'informations

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
IEEE COMPUTER GRAPHICS AND APPLICATIONS. vol. 11, no. 3, May 1991, NEW YORK US pages 47 - 55 , XP207660 G.NIELSON ET AL. 'VISUALIZING AND MODELING SCATTERED MULTIVARIATE DATA' *
'REFLEX USER'S GUIDE' 1985 , BORLAND , SCOTTS VALLEY, CA, USA *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2001003053A1 (fr) * 1999-06-30 2001-01-11 Bayes Information Technology Ltd. Procede et systeme de visualisation
US6873325B1 (en) 1999-06-30 2005-03-29 Bayes Information Technology, Ltd. Visualization method and visualization system
EP3460646A4 (fr) * 2016-05-19 2019-04-24 Sony Corporation Dispositif de traitement d'informations, programme et système de traitement d'informations

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