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Computational Art Therapy HAR/CDR

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  • Formāts: 294 pages, height x width x depth: 2750x2125x1.00 mm, weight: 2700 g
  • Izdošanas datums: 09-Jul-2017
  • Izdevniecība: Charles C Thomas Pub Ltd
  • ISBN-10: 0398091773
  • ISBN-13: 9780398091774
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Computational Art Therapy HAR/CDRPalielināt
  • Formāts: 294 pages, height x width x depth: 2750x2125x1.00 mm, weight: 2700 g
  • Izdošanas datums: 09-Jul-2017
  • Izdevniecība: Charles C Thomas Pub Ltd
  • ISBN-10: 0398091773
  • ISBN-13: 9780398091774
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9780398091774.html
Keywords:
This book explains how computer technologies can help art therapists improve their practice and advance the theory of art therapy. It describes statistical methods, computer functions, technologies in digital image processing, computer algorithms, methodologies in expert systems, and the Bayesian network, using illustrations, sample drawings, and case studies. It covers the computerized art evaluation of elements of drawings using the elements of the Computer Color-Related Elements Art Therapy Evaluation System (C_CREATES) (provided on the accompanying CD-ROM), and the computerized art interpretation of the drawer’s psychological state using expert systems, statistical regression models, and Bayesian networks, including application to differentiation and identification of psychological states and estimating levels of psychological disorder. Annotation ©2017 Ringgold, Inc., Portland, OR (protoview.com)
About the Author vii
Acknowledgments ix
Preface xiii
Prologue: Introduction to the Computational Art Therapy (CAT) Keynote
P.1 The need of computer technologies in the field of art therapy
P.1.1 Present status of computer technologies in art therapy
1(1)
P.1.2 Problems and difficulties in art therapy
2(1)
P.1.3 Computer technologies as a solution
3(1)
P.1.4 The definition of Computational Art Therapy (CAT)
4(1)
P.2 Computer technologies relevant to art therapy
P.2.1 Built-in functions of a computer
4(1)
P.2.2 Techniques of digital image processing
5(1)
P.2.3 Computer algorithm
6(1)
P.2.4 Expert system
6(1)
P.2.5 Statistical methods
7(1)
P.2.6 Bayesian network
8(2)
P.3 Taxonomy of color-related elements in the C_CREATES for art evaluation
P.3.1 Classification of evaluation elements in art therapy tools
10(3)
P.3.2 Reliability of art evaluation
13(2)
P.4 The computer systems for art interpretation
P.4.1 Traditional methods and computer systems for art interpretation
15(2)
P.4.2 Validity of art interpretation
17(1)
P.5 Organization of the book
18(4)
P.6 Discussion
22(7)
PART ONE ART EVALUATION
Chapter 1 Evaluation of Basic Elements in the Computerized Color-Related Elements Art Therapy Evaluation System (C_CREATES)(I) Abstract and Summary
1.1 Built-in functions of a computer
1.1.1 Color in art therapy
29(1)
1.1.2 Color recognition
30(2)
1.1.3 Color classification
32(2)
1.1.4 Edge detection
34(1)
1.2 Techniques in digital image processing
1.2.1 Noise removing
34(1)
1.2.2 Blurring
34(2)
1.2.3 Clustering
36(1)
1.2.4 Edge detection
36(2)
1.3 Evaluation of basic elements in the C_CREATES
1.3.1 Procedures
38(2)
1.3.2 Verifications of the C_CREATES
40(6)
1.4 Discussion
46(2)
Chapter 2 Evaluation of Basic Elements in the C_CREATES (II) Summary
2.1 Elements related with color definitions, space colored, and pattern coloring
48(2)
2.2 Primary /secondary, warm/cool, and complementary colors
2.2.1 Elements related with color definitions
50(1)
2.2.2 Definitions
51(1)
2.3 Number of colored grids and area of colored convex hull
2.3.1 Elements related with space colored
52(1)
2.3.2 Algorithms
53(2)
2.4 Completeness and accuracy
2.4.1 Elements related with pattern coloring
55(1)
2.4.2 Algorithms
56(2)
2.5 Discussion and conclusion
58(1)
Chapter 3 A Computer System for Rating Variety of Colors Summary
3.1 Importance of color-related elements
59(2)
3.2 Method
3.2.1 Rule
61(1)
3.2.2 Sample
61(3)
3.3 Results
3.3.1 Inter-rater reliability
64(2)
3.3.2 System validity
66(3)
3.4 Discussion
69(1)
Chapter 4 Judgment of Main Color Using Computer Algorithm Keynote
4.1 Introduction
70(3)
4.2 Procedure of main color judgment
4.2.1 Case examples
73(1)
4.2.2 Computer algorithms
73(3)
4.3 System verification
4.3.1 Inter-rater reliability
76(3)
4.3.2 System validity
79(1)
4.4 Discussion
80(1)
Chapter 5 Determination of Placement Using Techniques of Digital Image Processing Key points
5.1 The element of placement in art therapy tools
81(2)
5.2 Methods for edge detection and definition of placement category
5.2.1 Methods for edge detection
83(2)
5.2.2 Definitions of placement categories
85(1)
5.3 Determination of placement category
5.3.1 Information on placement category
86(1)
5.3.2 Information on other elements of drawings
87(1)
5.4 System verification
5.4.1 Sample examples
87(4)
5.4.2 Inter-rater reliability
91(1)
5.4.3 System validity
91(1)
5.4.4 Other useful information
91(1)
5.5 Discussion
92(1)
Chapter 6 Grading and Ranking Prominence of Color and Details of Drawing Using Regression Models Key point
6.1 Regression analysis
93(2)
6.2 Method and samples
95(1)
6.3 Evaluations by human raters and their inter-rater reliabilities
6.3.1 Grade
95(1)
6.3.2 Rank
96(4)
6.4 Evaluation by regression models
6.4.1 Grade
100(2)
6.4.2 Rank
102(2)
6.5 System validities
6.5.1 Grade
104(1)
6.5.2 Rank
105(1)
6.6 Discussion and conclusion
106(2)
Chapter 7 Evaluation of Space Usage in a Drawing and Degree of Concentration in a Pattern Coloring Key points
7.1 Importance of space usage and degree of concentration
108(3)
7.2 Regression models for the evaluation of space usage in grade and rank
7.2.1 Possible independent variables
111(3)
7.2.2 Inter-rater reliabilities in the evaluation of dependent variables
114(1)
7.2.3 Regression models
114(2)
7.2.4 System validity
116(1)
7.3 Regression model for the evaluation of concentration in rank
7.3.1 Sample pattern colorings
117(2)
7.3.2 Inter-rater reliability
119(1)
7.3.3 A regression model and its validity
119(2)
7.4 Discussion and conclusion
121(2)
Chapter 8 A Bridge from Part One to Part Two: Computerization of Art Evaluation and Its Application to Art Interpretation Abstract
8.1 An approach to developing a computerized evaluation system and its connection to art interpretation
123(1)
8.2 Computerization of the Face Stimulus Assessment (FSA)
8.2.1 The FSA
124(1)
8.2.2 Algorithms and criteria for each element
125(1)
8.2.3 Elements in the Computerized Face Stimulus Assessment (c_FSA)
126(3)
8.2.4 Reliability and validity of the c_FSA
129(1)
8.3 Application of the evaluation results in Part One to the interpretation in Part Two
8.3.1 Relationships between the space usage in the PPAT and severity, and degree of dementia
130(2)
8.3.2 Relationships of the five elements in the c_FSA
132(1)
8.4 Conclusion
133(4)
PART TWO ART INTERPRETATION
Chapter 9 An Expert System Approach to Art Interpretation Abstract
9.1 Various factors considered in art interpretation
137(2)
9.2 An expert system for art interpretation
9.2.1 System facilities
139(1)
9.2.2 Knowledge
139(3)
9.2.3 Reasoning process
142(4)
9.2.4 Advantages of the system
146(1)
9.2.5 System features
147(2)
9.3 Case study
149(1)
9.4 Discussion
150(2)
Chapter 10 Reasoning Process of an Expert System for Art Therapy Abstract
10.1 Modeling human decision process
152(2)
10.2 Process of diagnosis consisting of nine sub-processes
10.2.1 Requirements of art interpretation process in expert system
154(1)
10.2.2 Model of reasoning process
155(3)
10.3 Reliability, consistency, and learning abilities
158(3)
10.4 Knowledge base for each stage
161(2)
10.5 Case study
163(4)
10.6 Discussion
167(1)
Chapter 11 An Expert System for Interpreting the Structured Mandala Coloring (SMC) Drawings Abstract and summary
11.1 The Structured Mandala Coloring (SMC) as a subject of expert system
168(3)
11.2 Knowledge base
11.2.1 Knowledge expression
171(1)
11.2.2 Structure of knowledge base
172(4)
11.3 An expert system
176(2)
11.4 Case study
178(3)
11.5 Discussion
181(3)
Chapter 12 Computerized Kinetic Family Drawing Using Patterns (p_KFD) Summary
12.1 The Kinetic Family Drawing (KFD) as a subject of computerizing
184(3)
12.2 Questionnaires with fact base
187(1)
12.3 Composition and coloring
188(3)
12.4 Evaluation of elements and detection of changes
12.4.1 Evaluation of elements in the KFD
191(2)
12.4.2 Detection of changes in two KFD drawings
193(4)
12.5 Interpretation with knowledge base
197(4)
12.6 Discussion and conclusion
201(3)
Chapter 13 Computerized Structured Mandala Coloring (c_SMC) for Differentiation and Identification of Psychological States Using Statistical Methods Key Points
13.1 The Structured Mandala Coloring (SMC) as a subject of computerization
204(3)
13.2 Methods
13.2.1 Sampling
207(1)
13.2.2 Measurements
207(1)
13.2.3 Data analysis
208(1)
13.2.4 System validity
209(1)
13.3 Results
13.3.1 Differentiation of groups
209(1)
13.3.2 Identification of a group
210(2)
13.3.3 System volidity
212(2)
13.4 Discussion and conclusion
214(2)
Chapter 14 Statistical Models for Estimating Level of Psychological Disorder Abstract
14.1 Regression model to estimate degree of dementia using structured mandala
216(3)
14.2 Methodology
14.2.1 Application to dementia
219(1)
14.2.2 Model I: Estimation of levels of dementia
220(1)
14.2.3 Model II: Probability of severe dementia
220(1)
14.3 Results and system validity
14.3.1 Selection of independent variables and their effects in Model I
221(4)
14.3.2 Selection of independent variables and their effects in Model II
225(2)
14.4 Case studies
227(1)
14.5 Discussion, conclusion, and further study
228(4)
Chapter 15 A Statistical Approach to Comparing the Effectiveness of Several Art Therapy Tools in Estimating Level of a Psychological State Abstract
15.1 A generalized approach to compare effectiveness of several art therapy tools
232(2)
15.2 Approach: Regression model
234(1)
15.3 Case study
15.3.1 Subjects of psychological disorder and art therapy tools
235(2)
15.3.2 Independent variables
237(1)
15.3.3 Results
238(5)
15.4 Discussion and conclusion
243(2)
Chapter 16 Probabilistic Art Interpretation Using Bayesian Network Abstract and keynote
16.1 Probabilistic interpretation vs. deterministic interpretation
245(2)
16.2 Methods
247(3)
16.3 A Bayesian network-based art interpretation
250(2)
16.4 System verification
252(1)
16.5 Discussion and conclusion
253(2)
Epilogue Searching for the Advancement of Art Therapy 255(4)
Appendix: Companion S/W 259(11)
Glossary 270(2)
Copyright Permissions 272(3)
Bibliography 275(14)
Index 289