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Ambient Diagnostics [Pehme köide]

  • Formaat: Paperback / softback, 404 pages, kõrgus x laius: 234x156 mm, kaal: 453 g
  • Ilmumisaeg: 18-Oct-2019
  • Kirjastus: CRC Press
  • ISBN-10: 0367378086
  • ISBN-13: 9780367378080
Teised raamatud teemal:
Ambient DiagnosticsSuurem pilt
  • Formaat: Paperback / softback, 404 pages, kõrgus x laius: 234x156 mm, kaal: 453 g
  • Ilmumisaeg: 18-Oct-2019
  • Kirjastus: CRC Press
  • ISBN-10: 0367378086
  • ISBN-13: 9780367378080
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780367378080.html
Ambient Diagnostics addresses innovative methods for discovering patterns from affordable devices, such as mobile phones, watches, cameras, and game interfaces, to interpret multimedia data for personal health monitoring and diagnosis. This is the first comprehensive textbook on multidisciplinary innovations in affordable healthcarefrom sensory fusion, pattern detection, to classification.





Connecting the Dots

The material in this book combines sensing, pattern recognition, and visual design, and is divided into four parts, which cover fundamentals, multimedia intelligence, pervasive sensors, and crowdsourcing. The author describes basic pattern discovery models, sound, color, motion and video analytics, and pattern discovery from games and social networks. Each chapter contains the materials main concepts, as well as case studies, and extensive study questions.



















Contains overviews about diagnostic sensors on mobile phones





Reflects the rapidly growing platforms for remote sensing, gaming, and social networking





Incorporates cognitive tests such as fatigue detection





Includes pseudo code and sample code





Provides vision algorithms and multimedia analytics











Covers Multimedia Intelligence Extensively

Ambient Diagnostics includes concepts for ambient technologies such as point-and-search, the pill camera, active sensing with Kinect, digital human labs, negative and relative feature spaces, and semantic representations. The book also introduces methods for collective intelligence from online video games and social media.
Preface xvii
About the Author xxi
SECTION 1 Fundamentals
Chapter 1 Introduction
3(24)
1.1 What Is Ambient Diagnostics?
3(4)
1.2 Diagnostic Models
7(5)
1.3 Multimedia Intelligence
12(4)
1.4 Crowdsourcing
16(1)
1.5 Soft Sensors
17(3)
1.6 Science of Simplicity
20(1)
1.7 Personal Diagnoses
21(3)
1.8 Basic Algorithms
24(1)
1.9 Basic Tools
24(1)
1.10 Summary
24(3)
Problems
25(2)
Chapter 2 Data Transformation
27(22)
2.1 Introduction
27(1)
2.2 Early Discoveries of Heartbeat Patterns
27(2)
2.3 Transforms, Features, and Attributes
29(1)
2.4 Sequential Features
30(1)
2.5 Spatiotemporal Features
31(1)
2.6 Shape Features
32(4)
2.7 Imagery Features
36(1)
2.8 Frequency Domain Features
37(5)
2.9 Multiresolution Features
42(5)
2.10 Summary
47(2)
Problems
48(1)
Chapter 3 Pattern Recognition
49(26)
3.1 Introduction
49(1)
3.2 Similarities and Distances
49(4)
3.3 Clustering Methods
53(4)
3.4 Classification Methods
57(10)
3.5 Classifier Accuracy Measures
67(3)
3.6 Summary
70(5)
Problems
71(4)
SECTION 2 Multimedia Intelligence
Chapter 4 Sound Recognition
75(24)
4.1 Introduction
76(1)
4.2 Microphone Apps
76(1)
4.3 Modern Acoustic Transducers (Microphones)
77(2)
4.4 Frequency Response Characteristics
79(1)
4.5 Digital Audio File Formats
80(2)
4.6 Heart Sound Sensing
82(1)
4.7 Lung Sound Sensing
83(2)
4.8 Snore Meter
85(1)
4.9 Spectrogram
85(2)
4.10 Ambient Sound Analysis
87(3)
4.11 Sound Recognition
90(2)
4.12 Recognizing Asthma Sounds
92(1)
4.13 Peak Shift
93(1)
4.14 Feature Compression
94(1)
4.15 Regrouping
94(1)
4.16 Noise Issues
95(1)
4.17 Future Applications
96(1)
4.18 Summary
96(3)
Problems
97(2)
Chapter 5 Color Vision
99(24)
5.1 Introduction
99(1)
5.2 Color Sensing
99(1)
5.3 Human Color Vision
100(1)
5.4 Color Sensors
101(2)
5.5 Color-Matching Experiments
103(2)
5.6 Color Spaces
105(4)
5.7 Color Segmentation
109(3)
5.8 Color Consistency Calibration
112(2)
5.9 Surface Color Diagnosis
114(4)
5.10 Colorimetric Paper Sensor: Lab on Paper
118(1)
5.11 Colorimetric Smell Sensors
119(1)
5.12 Summary
120(3)
Problems
121(2)
Chapter 6 Kinect Sensors
123(24)
6.1 Introduction
123(1)
6.2 The Kinect Revolution
124(1)
6.3 How Does It Work?
125(2)
6.4 Object Tracking
127(4)
6.5 Gesture Alignment
131(5)
6.6 Gesture Recognition
136(2)
6.7 Surface Modeling
138(3)
6.8 Biometric Measurement
141(1)
6.9 Sound Source Location
142(1)
6.10 Summary
143(4)
Problems
144(3)
Chapter 7 Video Analysis
147(24)
7.1 Introduction
147(1)
7.2 Object Detection by Motion
147(5)
7.3 Object Tracking
152(2)
7.4 Shape Descriptions
154(5)
7.5 Visualization of Video Data
159(3)
7.6 Activity Recognition
162(2)
7.7 Color and Motion Amplification
164(4)
7.8 Summary
168(3)
Problems
168(3)
Chapter 8 Fatigue Detection
171(20)
8.1 Introduction
171(1)
8.2 Disease-Related Fatigue
171(1)
8.3 Vigilance Theories
172(1)
8.4 The Vigilance Clock
173(3)
8.5 Facial Fatigue Detection
176(2)
8.6 Passive Face Detection
178(2)
8.7 Passive Face Tracking
180(5)
8.8 Active Sensing for Detecting Blinking and Yawning
185(2)
8.9 Summary
187(4)
Problems
187(4)
SECTION 3 Pervasive Sensors
Chapter 9 Mobile Sensors
191(24)
9.1 Introduction
191(1)
9.2 Accelerometers
191(4)
9.3 Gyroscope
195(2)
9.4 Magnetic Field Sensor
197(1)
9.5 Orientation Sensor
198(1)
9.6 Touch Gesture Sensors
199(2)
9.7 Environmental Sensors
201(1)
9.8 Proximity Sensor
202(1)
9.9 Near-Field Communication Sensors
202(2)
9.10 GPS Sensors
204(1)
9.11 Wireless Fidelity Sensing
204(1)
9.12 Bluetooth Sensing
205(1)
9.13 Sensory Fusion
205(1)
9.14 Motion Classification
206(5)
9.15 Accessing Sensors on Mobile Phones
211(1)
9.16 Summary
212(3)
Problems
212(3)
Chapter 10 Body Media
215(24)
10.1 Introduction
215(1)
10.2 Emerging Wearable Sensors
215(1)
10.3 Body-Area Networks
216(1)
10.4 Brain-Computer Interface
217(6)
10.5 Epidermal Electronics (Smart Fiber)
223(7)
10.6 Pill Cameras
230(6)
10.7 Summary
236(3)
Problems
236(3)
Chapter 11 Pocket Microscopes
239(24)
11.1 Introduction
239(1)
11.2 The Amateur Expert
240(1)
11.3 Sizes of Microorganisms
241(1)
11.4 Mobile Phone Microscopes
242(3)
11.5 Digital Microscopes
245(1)
11.6 Spectrum Lighting
246(1)
11.7 Observing Yeast Cells
247(1)
11.8 Observing Parasitic Worms
248(1)
11.9 Time-Lapse Video
249(1)
11.10 Laser Holography
249(1)
11.11 Virtual Microscopy
250(4)
11.12 Labeling and Counting
254(5)
11.13 Usability Study
259(1)
11.14 Summary
260(3)
Problems
261(2)
Chapter 12 Personal Spectrometers
263(20)
12.1 Introduction
263(1)
12.2 Beer's Law
264(1)
12.3 Diffraction Grating
265(4)
12.4 DIY Spectrometer
269(2)
12.5 Analytical Algorithm
271(2)
12.6 Urine Sample Test
273(2)
12.7 Crowdsourcing Spectrometer
275(1)
12.8 Diagnostic Applications
276(2)
12.9 Summary
278(5)
Problems
279(4)
SECTION 4 Crowdsourcing
Chapter 13 Remote Sensing
283(20)
13.1 Introduction
283(1)
13.2 Remote Sensing in Public Space
283(2)
13.3 Human Body Segmentation
285(4)
13.4 Waist Perimeter and Body Mass Calculations
289(4)
13.5 Fuzzy Diagnostic Heuristics
293(3)
13.6 Digital Human Modeling
296(1)
13.7 Physically Augmented Virtual Human Model
297(1)
13.8 Surface Analysis
298(2)
13.9 Summary
300(3)
Problems
301(2)
Chapter 14 Games for Diagnoses
303(24)
14.1 Introduction
303(1)
14.2 Emerging Games for Diagnosis
303(6)
14.3 Anatomy of Game Engines
309(5)
14.4 Networking
314(1)
14.5 Finite-State Machine
314(1)
14.6 World Modeling
315(1)
14.7 Motion Capture and Control
316(1)
14.8 Game Displays
317(2)
14.9 Game Development Tool Kits
319(6)
14.10 Summary
325(2)
Problems
326(1)
Chapter 15 Social Media
327(22)
15.1 Introduction
327(1)
15.2 The Pregnant Man
327(1)
15.3 Relevancy Analysis
328(5)
15.4 Reputation Analysis
333(5)
15.5 Visualizing Social Networks
338(3)
15.6 Correlation Analysis
341(3)
15.7 Summary
344(5)
Problems
345(4)
SECTION 5 Appendices
A Sample Code
349(10)
B Further Readings
359(6)
Index 365
Yang Cai is a computer scientist at Carnegie Mellon University, where he has taught graduate courses in cognitive video, multimedia, human algorithms, creativity, and innovation process. Cai is the founder of the Visual Intelligence Studio and author of the emerging theories of instinctive computing, ambient diagnostics, and empathic computing. He has hosted international workshops on ambient intelligence for scientific discovery, instinctive computing, digital human modeling, and video intelligence. He has been working on research projects with the National Science Foundation, NASA, the Air Force Research Lab, and various industries.