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Biblioteca

MARC Lista (tabellare)
Cross-modal analysis of speech, gestures, gaze and facial expressions : COST Action 2102 International Conference Prague, Czech Republic, October 15-18, 2008 : revised selected and invited papers / / Anna Esposito, Robert Vích, editors
Cross-modal analysis of speech, gestures, gaze and facial expressions : COST Action 2102 International Conference Prague, Czech Republic, October 15-18, 2008 : revised selected and invited papers / / Anna Esposito, Robert Vích, editors
Edizione [1st ed. 2009.]
Pubbl/distr/stampa Berlin ; ; Heidelberg ; ; New York : , : Springer, , [2009]
Descrizione fisica 1 online resource (449 p.)
Disciplina 006.42
Collana Lecture notes in artificial intelligence
Soggetto topico Human face recognition (Computer science)
ISBN 1-282-33195-7
9786612331954
3-642-03320-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Emotions and ICT -- Cross-Fertilization between Studies on ICT Practices of Use and Cross-Modal Analysis of Verbal and Nonverbal Communication -- Theories without Heart -- Prosodic Characteristics and Emotional Meanings of Slovak Hot-Spot Words -- Affiliations, Emotion and the Mobile Phone -- Polish Emotional Speech Database – Recording and Preliminary Validation -- Towards a Framework of Critical Multimodal Analysis: Emotion in a Film Trailer -- Biosignal Based Emotion Analysis of Human-Agent Interactions -- Emotional Aspects in User Experience with Interactive Digital Television: A Case Study on Dyslexia Rehabilitation -- Investigation of Normalised Time of Increasing Vocal Fold Contact as a Discriminator of Emotional Voice Type -- Evaluation of Speech Emotion Classification Based on GMM and Data Fusion -- Spectral Flatness Analysis for Emotional Speech Synthesis and Transformation -- Verbal and Nonverbal Features of Computational Phonetics -- Voice Pleasantness of Female Voices and the Assessment of Physical Characteristics -- Technical and Phonetic Aspects of Speech Quality Assessment: The Case of Prosody Synthesis -- Syntactic Doubling: Some Data on Tuscan Italian -- Perception of Czech in Noise: Stability of Vowels -- Challenges in Segmenting the Czech Lateral Liquid -- Implications of Acoustic Variation for the Segmentation of the Czech Trill /r/ -- Voicing in Labial Plosives in Czech -- Normalization of the Vocalic Space -- Algorithmic and Theoretical Analysis of Multimodal Interfaces -- Gaze Behaviors for Virtual Crowd Characters -- Gestural Abstraction and Restatement: From Iconicity to Metaphor -- Preliminary Prosodic and Gestural Characteristics of Instructing Acts in Polish Task-Oriented Dialogues -- Polish Children’s Gesticulation in Narrating (Re-telling) a Cartoon -- Prediction of Learning Abilities Based on a Cross-Modal Evaluation of Non-verbal Mental Attributes Using Video-Game-Like Interfaces -- Automatic Sentence Modality Recognition in Children’s Speech, and Its Usage Potential in the Speech Therapy -- Supporting Engagement and Floor Control in Hybrid Meetings -- Behavioral Consistency Extraction for Face Verification -- Protecting Face Biometric DCT Templates by Means of Pseudo-random Permutations -- Facial Expressions Recognition from Image Sequences -- Czech Artificial Computerized Talking Head George -- An Investigation into Audiovisual Speech Correlation in Reverberant Noisy Environments -- Articulatory Speech Re-synthesis: Profiting from Natural Acoustic Speech Data -- A Blind Source Separation Based Approach for Speech Enhancement in Noisy and Reverberant Environment -- Quantitative Analysis of the Relative Local Speech Rate -- Czech Spontaneous Speech Collection and Annotation: The Database of Technical Lectures -- BSSGUI – A Package for Interactive Control of Blind Source Separation Algorithms in MATLAB -- Accuracy Analysis of Generalized Pronunciation Variant Selection in ASR Systems -- Analysis of the Possibilities to Adapt the Foreign Language Speech Recognition Engines for the Lithuanian Spoken Commands Recognition -- MLLR Transforms Based Speaker Recognition in Broadcast Streams.
Record Nr. UNISA-996465626503316
Berlin ; ; Heidelberg ; ; New York : , : Springer, , [2009]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Deep learning-based face analytics / / Nalini K. Ratha, Vishal M. Patel, Rama Chellappa, editors
Deep learning-based face analytics / / Nalini K. Ratha, Vishal M. Patel, Rama Chellappa, editors
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (VI, 407 p. 182 illus., 169 illus. in color.)
Disciplina 006.37
Collana Advances in Computer Vision and Pattern Recognition
Soggetto topico Human face recognition (Computer science)
Machine learning
ISBN 3-030-74697-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 1. Deep CNN Face Recognition: Looking at the Past and the Future -- 2. Face Segmentation, Face Swapping, and Their Effect on Face Recognition -- 3. Disentangled Representation Learning and its Application to Face Analytics -- 4. Learning 3D Face Morphable Model from In-the-wild Images -- 5. Deblurring Face Images using Deep Networks -- 6. Blind-Superresolution of Faces for Surveillance -- 7. Hashing a Face.
Record Nr. UNINA-9910495352903321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Deep learning-based face analytics / / Nalini K. Ratha, Vishal M. Patel, Rama Chellappa, editors
Deep learning-based face analytics / / Nalini K. Ratha, Vishal M. Patel, Rama Chellappa, editors
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (VI, 407 p. 182 illus., 169 illus. in color.)
Disciplina 006.37
Collana Advances in Computer Vision and Pattern Recognition
Soggetto topico Human face recognition (Computer science)
Machine learning
ISBN 3-030-74697-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 1. Deep CNN Face Recognition: Looking at the Past and the Future -- 2. Face Segmentation, Face Swapping, and Their Effect on Face Recognition -- 3. Disentangled Representation Learning and its Application to Face Analytics -- 4. Learning 3D Face Morphable Model from In-the-wild Images -- 5. Deblurring Face Images using Deep Networks -- 6. Blind-Superresolution of Faces for Surveillance -- 7. Hashing a Face.
Record Nr. UNISA-996464392103316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Dynamic faces [[electronic resource] ] : insights from experiments and computation / / edited by Cristóbal Curio, Heinrich H. Bülthoff, and Martin A. Giese ; foreword by Tomaso Poggio
Dynamic faces [[electronic resource] ] : insights from experiments and computation / / edited by Cristóbal Curio, Heinrich H. Bülthoff, and Martin A. Giese ; foreword by Tomaso Poggio
Pubbl/distr/stampa Cambridge, Mass., : MIT Press, c2011
Descrizione fisica 1 online resource (299 p.)
Disciplina 006.3/7
Altri autori (Persone) CurioCristóbal <1972->
BülthoffHeinrich H
GieseMartin A
PoggioTomaso
Soggetto topico Human face recognition (Computer science)
Soggetto genere / forma Electronic books.
ISBN 1-282-97839-X
9786612978395
0-262-28931-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Contents; Foreword; Introduction; I Psychophysics; 1 Is Dynamic Face Perception Primary?; 2 Memory for Moving Faces; 3 Investigating the Dynamic Characteristics Important for Face Recognition; 4 Recognition of Dynamic Facial Action Probed by Visual Adaptation; 5 Facial Motion and Facial Form; 6 Dynamic Facial Speech; II Physiology; 7 Dynamic Facial Signaling; 8 Engaging Neocortical Networks with Dynamic Faces; 9 Multimodal Studies Using Dynamic Faces; 10 Perception of Dynamic Facial Expressions and Gaze; 11 Moving and Being Moved; III Computation; 12 Analyzing Dynamic Faces
13 Elements for a Neural Theory of the Processing of Dynamic Faces14 Insights on Spontaneous Facial Expressions from Automatic Expression Measurement; 15 Real-Time Dissociation of Facial Appearance and Dynamics during Natural Conversation; 16 Markerless Tracking of Dynamic 3D Scans of Faces; Contributors; Index
Record Nr. UNINA-9910459816103321
Cambridge, Mass., : MIT Press, c2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Dynamic faces : insights from experiments and computation / / edited by Cristóbal Curio, Heinrich H. Bülthoff, and Martin A. Giese ; foreword by Tomaso Poggio
Dynamic faces : insights from experiments and computation / / edited by Cristóbal Curio, Heinrich H. Bülthoff, and Martin A. Giese ; foreword by Tomaso Poggio
Pubbl/distr/stampa Cambridge, Mass., : MIT Press, ©2011
Descrizione fisica 1 online resource (299 p.)
Disciplina 006.3/7
Altri autori (Persone) CurioCristóbal <1972->
BülthoffHeinrich H
GieseMartin A
Soggetto topico Human face recognition (Computer science)
Soggetto non controllato NEUROSCIENCE/Visual Neuroscience
NEUROSCIENCE/General
ISBN 1-282-97839-X
9786612978395
0-262-28931-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Contents; Foreword; Introduction; I Psychophysics; 1 Is Dynamic Face Perception Primary?; 2 Memory for Moving Faces; 3 Investigating the Dynamic Characteristics Important for Face Recognition; 4 Recognition of Dynamic Facial Action Probed by Visual Adaptation; 5 Facial Motion and Facial Form; 6 Dynamic Facial Speech; II Physiology; 7 Dynamic Facial Signaling; 8 Engaging Neocortical Networks with Dynamic Faces; 9 Multimodal Studies Using Dynamic Faces; 10 Perception of Dynamic Facial Expressions and Gaze; 11 Moving and Being Moved; III Computation; 12 Analyzing Dynamic Faces
13 Elements for a Neural Theory of the Processing of Dynamic Faces14 Insights on Spontaneous Facial Expressions from Automatic Expression Measurement; 15 Real-Time Dissociation of Facial Appearance and Dynamics during Natural Conversation; 16 Markerless Tracking of Dynamic 3D Scans of Faces; Contributors; Index
Record Nr. UNINA-9910789837203321
Cambridge, Mass., : MIT Press, ©2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Dynamic faces : insights from experiments and computation / / edited by Cristóbal Curio, Heinrich H. Bülthoff, and Martin A. Giese ; foreword by Tomaso Poggio
Dynamic faces : insights from experiments and computation / / edited by Cristóbal Curio, Heinrich H. Bülthoff, and Martin A. Giese ; foreword by Tomaso Poggio
Pubbl/distr/stampa Cambridge, Mass., : MIT Press, ©2011
Descrizione fisica 1 online resource (299 p.)
Disciplina 006.3/7
Altri autori (Persone) CurioCristóbal <1972->
BülthoffHeinrich H
GieseMartin A
Soggetto topico Human face recognition (Computer science)
Soggetto non controllato NEUROSCIENCE/Visual Neuroscience
NEUROSCIENCE/General
ISBN 1-282-97839-X
9786612978395
0-262-28931-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Contents; Foreword; Introduction; I Psychophysics; 1 Is Dynamic Face Perception Primary?; 2 Memory for Moving Faces; 3 Investigating the Dynamic Characteristics Important for Face Recognition; 4 Recognition of Dynamic Facial Action Probed by Visual Adaptation; 5 Facial Motion and Facial Form; 6 Dynamic Facial Speech; II Physiology; 7 Dynamic Facial Signaling; 8 Engaging Neocortical Networks with Dynamic Faces; 9 Multimodal Studies Using Dynamic Faces; 10 Perception of Dynamic Facial Expressions and Gaze; 11 Moving and Being Moved; III Computation; 12 Analyzing Dynamic Faces
13 Elements for a Neural Theory of the Processing of Dynamic Faces14 Insights on Spontaneous Facial Expressions from Automatic Expression Measurement; 15 Real-Time Dissociation of Facial Appearance and Dynamics during Natural Conversation; 16 Markerless Tracking of Dynamic 3D Scans of Faces; Contributors; Index
Record Nr. UNINA-9910810241803321
Cambridge, Mass., : MIT Press, ©2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Face analysis under uncontrolled conditions : from face detection to expression recognition / / Romain Belmonte and Benjamin Allaert
Face analysis under uncontrolled conditions : from face detection to expression recognition / / Romain Belmonte and Benjamin Allaert
Autore Belmonte Romain
Pubbl/distr/stampa Hoboken, NJ : , : John Wiley & Sons, Inc., , [2022]
Descrizione fisica 1 online resource (312 pages)
Disciplina 006.42
Soggetto topico Human face recognition (Computer science)
Image processing
ISBN 1-394-17385-7
1-394-17383-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Part 1. Facial Landmark Detection -- Introduction to Part 1 -- Chapter 1. Facial Landmark Detection -- 1.1. Facial landmark detection in still images -- 1.1.1. Generative approaches -- 1.1.2. Discriminative approaches -- 1.1.3. Deep learning approaches -- 1.1.4. Handling challenges -- 1.1.5. Summary -- 1.2. Extending facial landmark detection to videos -- 1.2.1. Tracking by detection -- 1.2.2. Box, landmark and pose tracking -- 1.2.3. Adaptive approaches -- 1.2.4. Joint approaches -- 1.2.5. Temporal constrained approaches -- 1.2.6. Summary -- 1.3. Discussion -- 1.4. References -- Chapter 2. Effectiveness of Facial Landmark Detection -- 2.1. Overview -- 2.2. Datasets and evaluation metrics -- 2.2.1. Image and video datasets -- 2.2.2. Face preprocessing and data augmentation -- 2.2.3. Evaluation metrics -- 2.2.4. Summary -- 2.3. Image and video benchmarks -- 2.3.1. Compiled results on 300W -- 2.3.2. Compiled results on 300VW -- 2.4. Cross-dataset benchmark -- 2.4.1. Evaluation protocol -- 2.4.2. Comparison of selected approaches -- 2.5. Discussion -- 2.6. References -- Chapter 3. Facial Landmark Detection with Spatio-temporal Modeling -- 3.1. Overview -- 3.2. Spatio-temporal modeling review -- 3.2.1. Hand-crafted approaches -- 3.2.2. Deep learning approaches -- 3.2.3. Summary -- 3.3. Architecture design -- 3.3.1. Coordinate regression networks -- 3.3.2. Heatmap regression networks -- 3.4. Experiments -- 3.4.1. Datasets and evaluation protocols -- 3.4.2. Implementation details -- 3.4.3. Evaluation on SNaP-2DFe -- 3.4.4. Evaluation on 300VW -- 3.4.5. Comparison with existing models -- 3.4.6. Qualitative results -- 3.4.7. Properties of the networks -- 3.5. Design investigations -- 3.5.1. Encoder-decoder -- 3.5.2. Complementarity between spatial and temporal information.
3.5.3. Complementarity between local and global motion -- 3.6. Discussion -- 3.7. References -- Conclusion to Part 1 -- Part 2. Facial Expression Analysis -- Introduction to Part 2 -- Chapter 4. Extraction of Facial Features -- 4.1. Introduction -- 4.2. Face detection -- 4.2.1. Point-of-interest detection algorithms -- 4.2.2. Face alignment approaches -- 4.2.3. Synthesis -- 4.3. Face normalization -- 4.3.1. Dealing with head pose variations -- 4.3.2. Dealing with facial occlusions -- 4.3.3. Synthesis -- 4.4. Extraction of visual features -- 4.4.1. Facial appearance features -- 4.4.2. Facial geometric features -- 4.4.3. Facial dynamics features -- 4.4.4. Facial segmentation models -- 4.4.5. Synthesis -- 4.5. Learning methods -- 4.5.1. Classification versus regression -- 4.5.2. Fusion model -- 4.5.3. Synthesis -- 4.6. Conclusion -- 4.7. References -- Chapter 5. Facial Expression Modeling -- 5.1. Introduction -- 5.2. Modeling of the affective state -- 5.2.1. Categorical modeling -- 5.2.2. Dimensional modeling -- 5.2.3. Synthesis -- 5.3. The challenges of facial expression recognition -- 5.3.1. The variation of the intensity of the expressions -- 5.3.2. Variation of facial movement -- 5.3.3. Synthesis -- 5.4. The learning databases -- 5.4.1. Improvement of learning data -- 5.4.2. Comparison of learning databases -- 5.4.3. Synthesis -- 5.5. Invariance to facial expression intensities -- 5.5.1. Macro-expression -- 5.5.2. Micro-expression -- 5.5.3. Synthesis -- 5.6. Invariance to facial movements -- 5.6.1. Pose variations (PV) and large displacements (LD) -- 5.6.2. Synthesis -- 5.7. Conclusion -- 5.8. References -- Chapter 6. Facial Motion Characteristics -- 6.1. Introduction -- 6.2. Characteristics of the facial movement -- 6.2.1. Local constraint of magnitude and direction -- 6.2.2. Local constraint of the motion distribution.
6.2.3. Motion propagation constraint -- 6.3. LMP -- 6.3.1. Local consistency of the movement -- 6.3.2. Consistency of local distribution -- 6.3.3. Coherence in the propagation of the movement -- 6.4. Conclusion -- 6.5. References -- Chapter 7. Micro- and Macro-Expression Analysis -- 7.1. Introduction -- 7.2. Definition of a facial segmentation model -- 7.3. Feature vector construction -- 7.3.1. Motion features vector -- 7.3.2. Geometric features vector -- 7.3.3. Features fusion -- 7.4. Recognition process -- 7.5. Evaluation on micro- and macro-expressions -- 7.5.1. Learning databases -- 7.5.2. Micro-expression recognition -- 7.5.3. Macro-expressions recognition -- 7.5.4. Synthesis of experiments on micro- and macro-expressions -- 7.6. Same expression with different intensities -- 7.6.1. Data preparation -- 7.6.2. Fractional time analysis -- 7.6.3. Analysis on a different time frame -- 7.6.4. Synthesis of experiments on activation segments -- 7.7. Conclusion -- 7.8. References -- Chapter 8. Towards Adaptation to Head Pose Variations -- 8.1. Introduction -- 8.2. Learning database challenges -- 8.3. Innovative acquisition system (SNaP-2DFe) -- 8.4. Evaluation of face normalization methods -- 8.4.1. Does the normalization preserve the facial geometry? -- 8.4.2. Does normalization preserve facial expressions? -- 8.5. Conclusion -- 8.6. References -- Conclusion to Part 2 -- List of Authors -- Index -- EULA.
Record Nr. UNINA-9910643860303321
Belmonte Romain  
Hoboken, NJ : , : John Wiley & Sons, Inc., , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Face analysis under uncontrolled conditions : from face detection to expression recognition / / Romain Belmonte and Benjamin Allaert
Face analysis under uncontrolled conditions : from face detection to expression recognition / / Romain Belmonte and Benjamin Allaert
Autore Belmonte Romain
Pubbl/distr/stampa Hoboken, NJ : , : John Wiley & Sons, Inc., , [2022]
Descrizione fisica 1 online resource (312 pages)
Disciplina 006.42
Collana Sciences. Image. Information seeking in images and videos
Soggetto topico Human face recognition (Computer science)
ISBN 1-394-17385-7
1-394-17383-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Part 1. Facial Landmark Detection -- Introduction to Part 1 -- Chapter 1. Facial Landmark Detection -- 1.1. Facial landmark detection in still images -- 1.1.1. Generative approaches -- 1.1.2. Discriminative approaches -- 1.1.3. Deep learning approaches -- 1.1.4. Handling challenges -- 1.1.5. Summary -- 1.2. Extending facial landmark detection to videos -- 1.2.1. Tracking by detection -- 1.2.2. Box, landmark and pose tracking -- 1.2.3. Adaptive approaches -- 1.2.4. Joint approaches -- 1.2.5. Temporal constrained approaches -- 1.2.6. Summary -- 1.3. Discussion -- 1.4. References -- Chapter 2. Effectiveness of Facial Landmark Detection -- 2.1. Overview -- 2.2. Datasets and evaluation metrics -- 2.2.1. Image and video datasets -- 2.2.2. Face preprocessing and data augmentation -- 2.2.3. Evaluation metrics -- 2.2.4. Summary -- 2.3. Image and video benchmarks -- 2.3.1. Compiled results on 300W -- 2.3.2. Compiled results on 300VW -- 2.4. Cross-dataset benchmark -- 2.4.1. Evaluation protocol -- 2.4.2. Comparison of selected approaches -- 2.5. Discussion -- 2.6. References -- Chapter 3. Facial Landmark Detection with Spatio-temporal Modeling -- 3.1. Overview -- 3.2. Spatio-temporal modeling review -- 3.2.1. Hand-crafted approaches -- 3.2.2. Deep learning approaches -- 3.2.3. Summary -- 3.3. Architecture design -- 3.3.1. Coordinate regression networks -- 3.3.2. Heatmap regression networks -- 3.4. Experiments -- 3.4.1. Datasets and evaluation protocols -- 3.4.2. Implementation details -- 3.4.3. Evaluation on SNaP-2DFe -- 3.4.4. Evaluation on 300VW -- 3.4.5. Comparison with existing models -- 3.4.6. Qualitative results -- 3.4.7. Properties of the networks -- 3.5. Design investigations -- 3.5.1. Encoder-decoder -- 3.5.2. Complementarity between spatial and temporal information.
3.5.3. Complementarity between local and global motion -- 3.6. Discussion -- 3.7. References -- Conclusion to Part 1 -- Part 2. Facial Expression Analysis -- Introduction to Part 2 -- Chapter 4. Extraction of Facial Features -- 4.1. Introduction -- 4.2. Face detection -- 4.2.1. Point-of-interest detection algorithms -- 4.2.2. Face alignment approaches -- 4.2.3. Synthesis -- 4.3. Face normalization -- 4.3.1. Dealing with head pose variations -- 4.3.2. Dealing with facial occlusions -- 4.3.3. Synthesis -- 4.4. Extraction of visual features -- 4.4.1. Facial appearance features -- 4.4.2. Facial geometric features -- 4.4.3. Facial dynamics features -- 4.4.4. Facial segmentation models -- 4.4.5. Synthesis -- 4.5. Learning methods -- 4.5.1. Classification versus regression -- 4.5.2. Fusion model -- 4.5.3. Synthesis -- 4.6. Conclusion -- 4.7. References -- Chapter 5. Facial Expression Modeling -- 5.1. Introduction -- 5.2. Modeling of the affective state -- 5.2.1. Categorical modeling -- 5.2.2. Dimensional modeling -- 5.2.3. Synthesis -- 5.3. The challenges of facial expression recognition -- 5.3.1. The variation of the intensity of the expressions -- 5.3.2. Variation of facial movement -- 5.3.3. Synthesis -- 5.4. The learning databases -- 5.4.1. Improvement of learning data -- 5.4.2. Comparison of learning databases -- 5.4.3. Synthesis -- 5.5. Invariance to facial expression intensities -- 5.5.1. Macro-expression -- 5.5.2. Micro-expression -- 5.5.3. Synthesis -- 5.6. Invariance to facial movements -- 5.6.1. Pose variations (PV) and large displacements (LD) -- 5.6.2. Synthesis -- 5.7. Conclusion -- 5.8. References -- Chapter 6. Facial Motion Characteristics -- 6.1. Introduction -- 6.2. Characteristics of the facial movement -- 6.2.1. Local constraint of magnitude and direction -- 6.2.2. Local constraint of the motion distribution.
6.2.3. Motion propagation constraint -- 6.3. LMP -- 6.3.1. Local consistency of the movement -- 6.3.2. Consistency of local distribution -- 6.3.3. Coherence in the propagation of the movement -- 6.4. Conclusion -- 6.5. References -- Chapter 7. Micro- and Macro-Expression Analysis -- 7.1. Introduction -- 7.2. Definition of a facial segmentation model -- 7.3. Feature vector construction -- 7.3.1. Motion features vector -- 7.3.2. Geometric features vector -- 7.3.3. Features fusion -- 7.4. Recognition process -- 7.5. Evaluation on micro- and macro-expressions -- 7.5.1. Learning databases -- 7.5.2. Micro-expression recognition -- 7.5.3. Macro-expressions recognition -- 7.5.4. Synthesis of experiments on micro- and macro-expressions -- 7.6. Same expression with different intensities -- 7.6.1. Data preparation -- 7.6.2. Fractional time analysis -- 7.6.3. Analysis on a different time frame -- 7.6.4. Synthesis of experiments on activation segments -- 7.7. Conclusion -- 7.8. References -- Chapter 8. Towards Adaptation to Head Pose Variations -- 8.1. Introduction -- 8.2. Learning database challenges -- 8.3. Innovative acquisition system (SNaP-2DFe) -- 8.4. Evaluation of face normalization methods -- 8.4.1. Does the normalization preserve the facial geometry? -- 8.4.2. Does normalization preserve facial expressions? -- 8.5. Conclusion -- 8.6. References -- Conclusion to Part 2 -- List of Authors -- Index -- EULA.
Record Nr. UNINA-9910830441903321
Belmonte Romain  
Hoboken, NJ : , : John Wiley & Sons, Inc., , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Face processing [[electronic resource] ] : advanced modeling and methods / / edited by Wenyi Zhao and Rama Chellappa
Face processing [[electronic resource] ] : advanced modeling and methods / / edited by Wenyi Zhao and Rama Chellappa
Pubbl/distr/stampa Amsterdam ; ; Boston, : Elsevier / Academic Press, c2006
Descrizione fisica 1 online resource (755 p.)
Disciplina 006.37
006.37 22
Altri autori (Persone) ZhaoWenyi
ChellappaRama
Soggetto topico Human face recognition (Computer science)
Biometric identification - Research
Soggetto genere / forma Electronic books.
ISBN 1-281-05319-8
9786611053192
0-08-048884-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Front Cover; FACE PROCESSING: Advanced Modeling and Methods; Copyright Page; Contents; Contributors; Preface; PART I: THE BASICS; Chapter 1. A Guided Tour of Face Processing; Chapter 2. Eigenfaces and Beyond; Chapter 3. Introduction to the Statistical Evaluation of Face-Recognition Algorithms; PART II: FACE MODELING; COMPUTATIONAL ASPECTS; Chapter 4. 3D Morphable Face Model, a Unified Approach for Analysis and Synthesis of Images; Chapter 5. Expression-Invariant Three-Dimensional Face Recognition; Chapter 6. 3D Face Modeling From Monocular Video Sequences
Chapter 7. Face Modeling by Information MaximizationPSYCHOPHYSICAL ASPECTS; Chapter 8. Face Recognition by Humans; Chapter 9. Predicting Human Performance for Face Recognition; Chapter 10. Spatial Distribution of Face and Object Representations in the Human Brain; PART III: ADVANCED METHODS; Chapter 11. On the Effect of Illumination and Face Recognition; Chapter 12. Modeling Illumination Variation with Spherical Harmonics; Chapter 13. A Multisubregion-Based Probabilistic Approach Toward Pose-Invariant Face Recognition
Chapter 14. Morphable Models for Training a Component-Based Face-Recognition SystemChapter 15. Model-Based Face Modeling and TrackingWith Application to Videoconferencing; Chapter 16. A survey of 3D and Multimodal 3D+2D Face Recognition; Chapter 17. Beyond One Still Image: Face Recognition from Multiple Still Images or Video Sequence; Chapter 18. Subset Modeling of Face Localization Error, Occlusion, and Expression; Chapter 19. Near Real-time Robust Face and Facial-Feature Detection with Information-Based Maximum Discrimination
Chapter 20. Current Landscape of Thermal Infrared Face RecognitionChapter 21. Multimodal Biometrics: Augmenting Face With Other Cues; Index
Record Nr. UNINA-9910458493703321
Amsterdam ; ; Boston, : Elsevier / Academic Press, c2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Face processing [[electronic resource] ] : advanced modeling and methods / / edited by Wenyi Zhao and Rama Chellappa
Face processing [[electronic resource] ] : advanced modeling and methods / / edited by Wenyi Zhao and Rama Chellappa
Pubbl/distr/stampa Amsterdam ; ; Boston, : Elsevier / Academic Press, c2006
Descrizione fisica 1 online resource (755 p.)
Disciplina 006.37
006.37 22
Altri autori (Persone) ZhaoWenyi
ChellappaRama
Soggetto topico Human face recognition (Computer science)
Biometric identification - Research
ISBN 1-281-05319-8
9786611053192
0-08-048884-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Front Cover; FACE PROCESSING: Advanced Modeling and Methods; Copyright Page; Contents; Contributors; Preface; PART I: THE BASICS; Chapter 1. A Guided Tour of Face Processing; Chapter 2. Eigenfaces and Beyond; Chapter 3. Introduction to the Statistical Evaluation of Face-Recognition Algorithms; PART II: FACE MODELING; COMPUTATIONAL ASPECTS; Chapter 4. 3D Morphable Face Model, a Unified Approach for Analysis and Synthesis of Images; Chapter 5. Expression-Invariant Three-Dimensional Face Recognition; Chapter 6. 3D Face Modeling From Monocular Video Sequences
Chapter 7. Face Modeling by Information MaximizationPSYCHOPHYSICAL ASPECTS; Chapter 8. Face Recognition by Humans; Chapter 9. Predicting Human Performance for Face Recognition; Chapter 10. Spatial Distribution of Face and Object Representations in the Human Brain; PART III: ADVANCED METHODS; Chapter 11. On the Effect of Illumination and Face Recognition; Chapter 12. Modeling Illumination Variation with Spherical Harmonics; Chapter 13. A Multisubregion-Based Probabilistic Approach Toward Pose-Invariant Face Recognition
Chapter 14. Morphable Models for Training a Component-Based Face-Recognition SystemChapter 15. Model-Based Face Modeling and TrackingWith Application to Videoconferencing; Chapter 16. A survey of 3D and Multimodal 3D+2D Face Recognition; Chapter 17. Beyond One Still Image: Face Recognition from Multiple Still Images or Video Sequence; Chapter 18. Subset Modeling of Face Localization Error, Occlusion, and Expression; Chapter 19. Near Real-time Robust Face and Facial-Feature Detection with Information-Based Maximum Discrimination
Chapter 20. Current Landscape of Thermal Infrared Face RecognitionChapter 21. Multimodal Biometrics: Augmenting Face With Other Cues; Index
Record Nr. UNINA-9910784547903321
Amsterdam ; ; Boston, : Elsevier / Academic Press, c2006
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