Face Detection and Gesture Recognition for Human-Computer Interaction
(Sprache: Englisch)
With the ubiquity of new information technology and media, more effective and friendly methods for human computer interaction (HCI) are being developed which do not rely on traditional devices such as keyboards, mice and displays. The first step for any...
Leider schon ausverkauft
versandkostenfrei
Buch (Kartoniert)
112.34 €
Produktdetails
Produktinformationen zu „Face Detection and Gesture Recognition for Human-Computer Interaction “
With the ubiquity of new information technology and media, more effective and friendly methods for human computer interaction (HCI) are being developed which do not rely on traditional devices such as keyboards, mice and displays. The first step for any intelligent HCI system is face detection, and one of most friendly HCI systems is hand gesture.
Face Detection and Gesture Recognition for Human-Computer Interaction introduces the frontiers of vision-based interfaces for intelligent human computer interaction with focus on two main issues: face detection and gesture recognition. The first part of the book reviews and discusses existing face detection methods, followed by a discussion on future research. Performance evaluation issues on the face detection methods are also addressed. The second part discusses an interesting hand gesture recognition method based on a generic motion segmentation algorithm. The system has been tested with gestures from American Sign Language with promising results. We conclude this book with comments on future work in face detection and hand gesture recognition.
Face Detection and Gesture Recognition for Human-Computer Interaction will interest those working in vision-based interfaces for intelligent human computer interaction. It also contains a comprehensive survey on existing face detection methods, which will serve as the entry point for new researchers embarking on such topics. Furthermore, this book also covers in-depth discussion on motion segmentation algorithms and applications, which will benefit more seasoned graduate students or researchers interested in motion pattern recognition.
Face Detection and Gesture Recognition for Human-Computer Interaction introduces the frontiers of vision-based interfaces for intelligent human computer interaction with focus on two main issues: face detection and gesture recognition. The first part of the book reviews and discusses existing face detection methods, followed by a discussion on future research. Performance evaluation issues on the face detection methods are also addressed. The second part discusses an interesting hand gesture recognition method based on a generic motion segmentation algorithm. The system has been tested with gestures from American Sign Language with promising results. We conclude this book with comments on future work in face detection and hand gesture recognition.
Face Detection and Gesture Recognition for Human-Computer Interaction will interest those working in vision-based interfaces for intelligent human computer interaction. It also contains a comprehensive survey on existing face detection methods, which will serve as the entry point for new researchers embarking on such topics. Furthermore, this book also covers in-depth discussion on motion segmentation algorithms and applications, which will benefit more seasoned graduate students or researchers interested in motion pattern recognition.
Klappentext zu „Face Detection and Gesture Recognition for Human-Computer Interaction “
Traditionally, scientific fields have defined boundaries, and scientists work on research problems within those boundaries. However, from time to time those boundaries get shifted or blurred to evolve new fields. For instance, the original goal of computer vision was to understand a single image of a scene, by identifying objects, their structure, and spatial arrangements. This has been referred to as image understanding. Recently, computer vision has gradually been making the transition away from understanding single images to analyzing image sequences, or video understanding. Video understanding deals with understanding of video sequences, e. g. , recognition of gestures, activities, facial expressions, etc. The main shift in the classic paradigm has been from the recognition of static objects in the scene to motion-based recognition of actions and events. Video understanding has overlapping research problems with other fields, therefore blurring the fixed boundaries. Computer graphics, image processing, and video databases have obvious overlap with computer vision. The main goal of computer graphics is to gener ate and animate realistic looking images, and videos. Researchers in computer graphics are increasingly employing techniques from computer vision to gen erate the synthetic imagery. A good example of this is image-based rendering and modeling techniques, in which geometry, appearance, and lighting is de rived from real images using computer vision techniques. Here the shift is from synthesis to analysis followed by synthesis.
Inhaltsverzeichnis zu „Face Detection and Gesture Recognition for Human-Computer Interaction “
1. Introduction.- 1. Face Detection.- 2. Gesture Recognition.- 3. Book Overview.- 2. Detecting Faces in Still Images.- 1. Introduction.- 2. Detecting Faces In A Single Image.- 3. Face Image Databases and Performance Evaluation.- 4. Discussion and Conclusion.- 3. Recognizing Hand Gestures Using Motion Trajectories.- 1. Introduction.- 2. Motivation and Approach.- 3. Motion Segmentation.- 4. Skin Color Model.- 5. Geometric Analysis.- 6. Motion Trajectories.- 7. Recognizing Motion Patterns Using Time-Delay Neural Network.- 8. Experiments.- 9. Discussion and Conclusion.- 4. Skin Color Model.- 1. Proposed Mixture Model.- 2. Statistical Tests.- 3. Experimental Results.- 4. Applications.- 5. Discussion and Conclusion.- 5. Face Detection Using Multimodal Density Models.- 1. Introduction.- 2. Previous Work.- 3. Mixture of Factor Analyzers.- 4. Mixture of Linear Spaces Using Fisher's Linear Discriminant.- 5. Experiments.- 6. Discussion and Conclusion.- 6. Learning to Detect Faces with SNoW.- 1. Introduction.- 2. Previous Work.- 3. SNoW Learning Architecture.- 4. Learning to Detect Faces.- 5. Empirical Results.- 6. Analyzing SNoW: Theoretical and Empirical Results.- 7. Generation and Efficiency.- 8. Discussion and Conclusion.- 7. Conclusion and Future Work.- 1. Conclusion.- 2. Future Work.- Appendices.- A- Covariance of Two Normally Distributed Variables.- B- Conditional Distributions of Multiple Correlation Coefficient.- References.
Bibliographische Angaben
- Autoren: Ming-Hsuan Yang , Narendra Ahuja
- 2012, Softcover reprint of the original 1st ed. 2001, XII, 182 Seiten, Maße: 15,6 x 23,6 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 146135546X
- ISBN-13: 9781461355465
Sprache:
Englisch
Kommentar zu "Face Detection and Gesture Recognition for Human-Computer Interaction"
0 Gebrauchte Artikel zu „Face Detection and Gesture Recognition for Human-Computer Interaction“
Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
---|
Schreiben Sie einen Kommentar zu "Face Detection and Gesture Recognition for Human-Computer Interaction".
Kommentar verfassen