Changeset 277 for trunk/VUT/doc/SciReport/introduction.tex

Timestamp:

09/16/05 10:41:52 (19 years ago)

Author:

bittner

Message:

changes in the structure: renamed tools to algorithms

File:

• trunk/VUT/doc/SciReport/introduction.tex (modified) (6 diffs)

trunk/VUT/doc/SciReport/introduction.tex

@@ -1 +1 @@
 \chapter{Introduction}%\chapter
 
-\label{chap:overview}
-\label{chap:classes}
-
- This chapter provides introduction to visibility problems and
-algorithms for computer graphics. In particular it presents a taxonomy
-of visibility problems and algorithms. We discuss typical visibility
-problems encountered in computer graphics including their relation to
-the presented taxonomy. Finally, we classify the later described
-visibility tools according to the presented taxonomy.
-
+\label{chap:introduction}
 
 \section{Structure of the report}
+
+  The report consists of two introductory chapters, which provide a
+ theoretical background for description of the algorithms, and three
+ chapters dealing with the actual visibility algorithms.
+
+  This chapter provides an introduction to visibility by using a
+ taxonomy of visibility problems and algorithms. The taxonomy is used
+ to classify the later described visibility
+ algorithms. Chapter~\ref{chap:analysis} provides an analysis of
+ visibility in 2D and 3D polygonal scenes. This analysis also includes
+ formal description of visibility using \plucker coordinates of
+ lines. \plucker coordinates are exploited later in algorithms for
+ mutual visibility verification (Chapter~\ref{chap:mutual}).
+
+ Chapter~\ref{chap:online} describes a visibility culling algorithm
+ used to implement the online visibility culling module. This
+ algorithm can be used accelerate rendering of fully dynamic scenes
+ using recent graphics hardware.  Chapter~\ref{chap:sampling}
+ describes global visibility sampling algorithm which forms a core of
+ the PVS computation module. This chapter also describes view space
+ partitioning algorithms used in close relation with the PVS
+ computation. Finally, Chapter~\ref{chap:mutual} describes mutual
+ visibility verification algorithms, which are used by the PVS
+ computation module to generate the final solution for precomputed
+ visibility.
+
 
 
@@ -127 +144 @@
 we obtain a vector that represents the same line $l$. More details
 about this singularity-free mapping will be discussed in
-Chapter~\ref{chap:vfr2d}.
+Chapter~\ref{chap:analysis}.
 
 
@@ -207 +224 @@
 
  Although the \plucker coordinates need more coefficients they have no
-singularity and preserve some linearities: lines intersecting a set of 
-lines in 3D correspond to an intersection of 5D hyperplanes. More details
-on \plucker coordinates will be discussed in
-Chapters~\ref{chap:vfr25d} and~\ref{chap:vfr3d} where they are used to
-solve the from-region visibility problem.
+singularity and preserve some linearities: lines intersecting a set of
+lines in 3D correspond to an intersection of 5D hyperplanes. More
+details on \plucker coordinates will be discussed in
+Chapter~\ref{chap:analysis} and Chapter~\ref{chap:mutual} where they
+are used to solve the from-region visibility problem.
 
   To sum up: In 3D there are four degrees of freedom in the
@@ -627 +644 @@
 the nature of the given problem and it should assist in finding
 relationships between visibility problems and algorithms in different
-application areas.  The tools address the following classes of
+application areas.  The algorithms address the following classes of
 visibility problems:
 
@@ -641 +658 @@
 discussed important steps in the design of a visibility algorithm that
 should also assist in understanding the quality of a visibility
-algorithm. According to the classification the tools address
-algorithms with the following properties:
+algorithm. According to the classification the visibility algorithms
+described later in the report address algorithms with the following
+properties:
 
 \begin{itemize}
 \item Domain:
   \begin{itemize}
-  \item viewpoint (online culling tool),
-  \item global visibility (global visibility sampling tool)
-  \item polygon or polyhedron (mutual visibility tool)
+  \item viewpoint (online visibility culling),
+  \item global visibility (global visibility sampling)
+  \item polygon or polyhedron (mutual visibility verification)
   \end{itemize}
 \item Scene restrictions (occluders):
@@ -671 +689 @@
 \item Solution space:
   \begin{itemize}
-  \item discrete (online culling tool, global visibility sampling tool, conservative and approximate algorithm from the mutual visibility tool)
-  \item continuous (exact algorithm from mutual visibility tool)
+  \item discrete (online visibility culling, global visibility sampling, conservative and approximate algorithm from the mutual visibility verification)
+  \item continuous (exact algorithm from mutual visibility verification)
   \end{itemize}
-  \item Solution space data structures: viewport (online culling tool), ray stack (global visibility sampling tool, conservative and approximate algorithm from the mutual visibility tool), BSP tree (exact algorithm from the mutual visibility tool)
+  \item Solution space data structures: viewport (online visibility culling), ray stack (global visibility sampling, conservative and approximate algorithm from the mutual visibility verification), BSP tree (exact algorithm from the mutual visibility verification)
   \item Use of coherence of visibility:
     \begin{itemize}
-    \item spatial coherence (all tools)
-    \item temporal coherence (online culling tool)
+    \item spatial coherence (all algorithms)
+    \item temporal coherence (online visibility culling)
     \end{itemize}
-  \item Output sensitivity: expected in practice (all tools)
-  \item Acceleration data structure: kD-tree (all tools)
-  \item Use of graphics hardware: online culling tool
+  \item Output sensitivity: expected in practice (all algorithms)
+  \item Acceleration data structure: kD-tree (all algorithms)
+  \item Use of graphics hardware: online visibility culling
   \end{itemize}