Gesture-Based Interaction with Time-of-Flight Cameras

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CHAPTER 2. TIME-OF-FLIGHT CAMERAS 2.7.6 Multi-Camera Setups The use of TOF cameras operating at the same modulation frequency in a configu- ration where light from one camera’s illumination unit can reach the sensor of the other camera corrupts the range measurement. This is due to the fact that the sensor cannot disambiguate between the phase shift induced by its own illumination unit and that of another camera. A straight forward way of circumventing this problem is to run the cameras at different demodulation frequencies. The demodulation approach to measuring the phase shift responds only to a very narrow band of frequencies near the modulation frequency; all other frequencies will merely appear as an increase in background illumination (Lange, 2000). A second solution to using several cameras in the same environment is to mod- ulate the illumination by a pseudo-noise signal. In case each camera uses a different code, the sensor will only detect the phase shift corresponding to its own emitted signal (Heinol, 2001). 26
Part II Algorithms 27
Page 1 and 2: Aus dem Institut für Neuro- und Bi
Page 3 and 4: Contents Acknowledgements vi I Intr
Page 5 and 6: CONTENTS 7.3.2 Sparse Features . .
Page 7: Acknowledgements There are a number
Page 11 and 12: 1 Introduction Nowadays, computers
Page 13 and 14: the scene (typically with light nea
Page 15 and 16: 2.1 Introduction 2 Time-of-Flight C
Page 17 and 18: 2.2. STATE-OF-THE-ART TOF SENSORS r
Page 19 and 20: 2.3. ALTERNATIVE OPTICAL RANGE IMAG
Page 21 and 22: 2.3. ALTERNATIVE OPTICAL RANGE IMAG
Page 23 and 24: 2.4 Measurement Principle 2.4. MEAS
Page 25 and 26: .I(t) .A .B . .A0 .A1 .A2 .A3 2.5.
Page 27 and 28: 2.5. TECHNICAL REALIZATION form H(f
Page 29 and 30: 2.6. MEASUREMENT ACCURACY the name
Page 31 and 32: 2.7 Limitations 2.7. LIMITATIONS As
Page 33: 2.7. LIMITATIONS objects than the i
Page 38 and 39: CHAPTER 3. INTRODUCTION straint: If
Page 40 and 41: CHAPTER 3. INTRODUCTION the class i
Page 42 and 43: CHAPTER 4. SHADING CONSTRAINT Besid
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Page 46 and 47: CHAPTER 4. SHADING CONSTRAINT 4.2.3
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Page 60 and 61: CHAPTER 5. SEGMENTATION (a) (b) (c)
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Page 67 and 68: 6.1 Introduction 6 Pose Estimation
Page 69 and 70: 6.2. METHOD resolve disambiguities
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Page 75 and 76: 6.3. RESULTS exactly which part of
Page 77 and 78: 6.4. DISCUSSION learning. As a resu
Page 79 and 80: 7 Features In image processing, the
Page 81 and 82: The first type of feature is relate
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7.1. GEOMETRIC INVARIANTS The featu
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4 3 ǫ2 2 5 ×10−3 1 7.1. GEOMETR
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7.1. GEOMETRIC INVARIANTS Figure 7.
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7.1. GEOMETRIC INVARIANTS We were a
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7.2. SCALE INVARIANT FEATURES measu
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an algorithm for the fast evaluatio
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7.2. SCALE INVARIANT FEATURES the o
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7.2. SCALE INVARIANT FEATURES exhib
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detection rate detection rate 1 0.8
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7.2. MULTIMODAL SPARSE FEATURES 7.3
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7.3. MULTIMODAL SPARSE FEATURES Fig
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7.3. MULTIMODAL SPARSE FEATURES Fig
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7.3. MULTIMODAL SPARSE FEATURES eac
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7.3. MULTIMODAL SPARSE FEATURES tem
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false positive rate 0.4 0.35 0.3 0.
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7.3. MULTIMODAL SPARSE FEATURES thi
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7.4. LOCAL RANGE FLOW FOR HUMAN GES
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Part III Applications 119
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CHAPTER 8. INTRODUCTION an alternat
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CHAPTER 9. FACIAL FEATURE TRACKING
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CHAPTER 9. FACIAL FEATURE TRACKING
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10.1 Introduction 10 Gesture-Based
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10.2. METHOD scenarios: One, where
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10.2. METHOD Figure 10.3: Segmented
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Table 10.1: Interpretation of point
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corner along the ray. 10.2. METHOD
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600 500 400 300 200 100 0 0 10 20 3
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10.4. DISCUSSION tention here was t
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CHAPTER 11. DEPTH OF FIELD BASED ON
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CHAPTER 12. CONCLUSION alization of
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Bibliography ARTTS 3D TOF Database.
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BIBLIOGRAPHY James R. Diebel and Se
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BIBLIOGRAPHY ence on Computer Visio
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BIBLIOGRAPHY Stefan Kunis and Danie
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BIBLIOGRAPHY Thierry Oggier, Michae
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BIBLIOGRAPHY Rudolf Schwarte, Horst
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BIBLIOGRAPHY ’06: Proceedings of
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modulation frequency, 8, 23, 26 Mon
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Gesture-Based Interaction with Time-of-Flight Cameras

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