Computer graphics processing and selective visual display system – Display driving control circuitry – Controlling the condition of display elements
Reexamination Certificate
2000-07-10
2003-10-28
Cabeca, John (Department: 2173)
Computer graphics processing and selective visual display system
Display driving control circuitry
Controlling the condition of display elements
C345S440000
Reexamination Certificate
active
06639614
ABSTRACT:
FIELD OF INVENTION
The present invention relates to graphical and auditory presentation of data, particularly for exploiting human pattern recognition.
BACKGROUND
The field of information visualization includes the use of graphs to convey information in a useful manner. Appropriate information displays can bring life to otherwise inert matrices or streams of numbers. Human perception and recognition of data trends can be facilitated through construction of comprehensible graphs. This trend perception is especially important when given large amounts of multi-variate data from which useful information must be quickly derived. Depending upon the environment and the importance of the decisions to be made, even the best information can become overwhelming. An example of one such environment is a fast-paced stock trading room where financial analysts are expected to quickly assess various online sources of information and make irrevocable decisions that can effect their very careers. Other situations arise in civil emergencies where an uninformed decision could jeopardize lives. The computer industry has generated a number of tools for coping with problems such as these.
Our brains allow us to do many things that defy even the most complex artificial systems. At the fore is our ability to organize a diverse range of information into relatively simple patterns and to monitor these patterns for outliers; cases that break ranks with the majority. The brain is the best “pattern detector” in existence. The conventional data visualization tools have failed to take advantage of the various cognitive and perceptual powers of the brain in any structured manner.
A graph is a visual display that illustrates one or more relationships among numbers. The best graphs are those that permit a visual pattern, trend or comparison to be quickly and accurately comprehended by a human reader. A poorly designed or constructed graph can be difficult to decipher properly, and could result in contusion or erroneous conclusions. Based upon knowledge of the particular audience, coupled with an understanding of human perception and cognition, a certain craftsmanship can be brought to bear upon the task.
Application of empirical findings from research on human cognition and perception to creation of graphs is explored in Stephen M. Kosslyn's book, “Elements of Graph Design,” (W.H. Freeman & Co., 1994), which is incorporated herein by reference. The author evaluates many of the factors that should be considered when selecting a graph format to present specific content for a specific purpose, and derives a set of principles having a basis in the physiological psychology of human cognition and perception. Exploitation of these principles when formulating a graphical presentation can dramatically improve the useful information content without appreciable increase in visual complexity. The author derives a list of principles that provide a framework against which to calibrate the relative effectiveness of various approaches to data visualization. In general, the principles can be divided into three sections: one regarding the way in which we actively organize and interpret what we see; another regarding how meaning is derived from visual displays; and a third related to memory and processing limitations related to proper interpretation. These same principles also apply directly to patterns of sounds.
One approach for display of information is disclosed in U.S. Pat. No. 5,671,381 issued to Strasnick. A three-dimensional, virtual reality display space is created to contain objects that represent blocks of data as 3-D bar-charts. Attributes of the data are mapped to visible or audible characteristics, such as an icon having a specific size or color. The spatial relationship and connecting lines between icons in the landscape represent structural relationships that exist in the underlying data, with the ground plane representing a numerical value as a common surface plane. Artificial perspective (with object compression near the horizon) adds to the realism of the view. A user can arrange the objects according to a preferred lexical order, and then “tour” across the landscape to browse or search for particular data items or relationships.
There are many disadvantages of this method of visualization. For one thing, the data representations are purely artificial, much like a two-dimensional bar-chart with its necessarily limited information bandwidth. A static hierarchical tree paradigm dictates the arrangements between the icons, illustrated by cluttered linkage lines. In essence, the user can merely navigate through a sea of bar charts illustrating the size and age of files, or similarly benign parameters. There is no means for indicating any data changes, nor their magnitude, relevance, or direction. Given the lack of change information, it would be impossible to detect any patterns of changes among the data sets. Furthermore, sound is implemented solely as a “warning tone” triggered when the user's cursor touches a file icon having a predetermined attribute. There is no selection from a variety of meaningful sounds, or any concept of spatial orientation, intensity, or inherent recognition of the sound's meaning, other than its mere occurrence.
Significantly, the system relies upon the virtual (i.e., artificial) reality context, a computationally complex, and visually distracting data display. Virtual reality (VR) attempts to replicate physical reality, where the better the VR system, the better the rendition. Visualizations of this type accentuate the details at the expense of data comprehension. As described in Kosslyn's “Elements of Graph Design”, human users can reliably process only a limited amount of visual information at one time, depending on a number of psychological factors including relevance and alertness. It takes additional effort for the mind to construct a 3-D perceptual organization of random icon meanings and orientations, especially when they are made even less intelligible by the artificial variations and distortions constantly introduced by “navigating.” A VR display contaminated with irrelevant or overly detailed information may actually reduce the ability to properly perceive the data patterns of most interest.
A similar arrangement, specifically addressed to visualization of information useful to money managers, is disclosed in U.S. Pat. Nos. 5,675,746, and 5,774,878, both issued to Marshall. In these and related patents, so-called 3-D “metaphors” are used to represent data in a virtual reality setting, where characteristics of each metaphorical object are determined by the corresponding data. The shape, color and rotation of each object may change according to the data, or to highlight criteria selected by the user. The location of the object may represent the source of the information (e.g., a selected market information feed), or a collective similarity (e.g., industry groups). The user may then “fly” among the objects to observe their characteristics more closely. For example, objects “floating” above the perceptual ground plane could represent data for stocks trading “above average.” The respective meaning of sounds, shapes and movement of 3-D objects are specified by the system configuration, although no particular arrangements are described.
Many of the disadvantages of this system relate to the limited visualization mechanisms employable. The arrangement of icons is according to a predetermined set of three-dimensional axes. The icons themselves have corresponding shape, size and color that are purely arbitrary and which lend very little to any inherent perception of their respective value. The portrayal of spinning, colored or pulsating icons merely represent data or data trends that have already been calculated. The totally abstract landscape does not lend itself to evaluating any recognizable objects, let alone interactions or patterns. There is nothing in the virtual reality arrangement to facilitate recognition of “outliers”, i.e., the few non-conforming data se
Ganis Giorgio
Kosslyn Stephen Michael
Rosenberg Robin Sue
Brown Rudnick Berlack & Israels LLP
Cabeca John
Detwiler Brian
Michaelis Brian L.
Quinn Joseph P.
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