Keywords:
- Alcohol
- Alcohol Consumption
- alcohol use
- Ambiance
- App-based survey
- Archaeology
- Assessment reactivity
- attractiveness
- attrition
- audio-visual feature extraction
- behavior
- BERT
- Big-Five
- booktube
- Casual Drinking
- Characterizing small groups
- Citizen Sourcing
- classifiers
- clustering
- cohesion
- collective classification
- Computational linguistics
- computer algorithm
- Computer Vision
- Convolutional Neural Networks
- corpus
- Crowdsourcing
- Cultural heritage
- data collection
- deep learning
- depression detection
- developing country
- Differential Privacy
- digital biomarker
- Dimensionality reduction
- diversity
- domain adaptation
- Drink size
- Drinking behaviours
- drinking context
- Eating Behavior
- Ecological momentary assessment
- Ecological momentary assessment (EMA)
- Emergent leadership
- Emerging power hierarchies
- Epigraphy
- explainability
- Facial & Body landmarks
- first impressions
- Flickr groups LDA
- Flickr PLSA topic-model communities
- Food Consumption
- food diaries
- foursquare
- Gestures
- Graph Convolutional Networks
- Graph Neural Networks
- Graph Representation Learning
- group interaction
- Group performance.
- health
- Heavy Drinking
- hieroglyph
- hirability
- Histogram of orientation
- Home Spaces
- HOOSC
- human mobility
- image retrieval
- impressions
- indexing
- information visualization
- Inter-pretable Models
- interaction
- Interview
- job interviews
- keyframe extraction
- language
- Language Production
- language style
- late-life depression
- Lausanne Data Collection Campaign
- LIWC
- location-based social networks
- loneliness
- Long-tail data distribution
- machine learning
- Maya civilization
- Maya culture
- Maya glyph
- maya glyphs
- meal
- meetings
- Mental Lexicon
- mHealth
- Mobile Crowdsensing
- mobile crowdsourcing
- mobile mining
- mobile phone data
- mobile sensing
- mobile survey
- mobility models
- model adaptation
- mood
- motion capture
- multimodal cues
- Multimodal interaction
- narcissism
- Natural conversation
- natural language porcessing
- neural networks
- Nightlife
- nonverbal be- havior
- Nonverbal behavior
- online video
- passive sensing
- perceived dominance
- performance
- Personality
- personality impressions
- Personality traits inference
- personalized service
- pervasive computing
- Physical Activity
- Picture annotation
- place extraction
- place labeling
- place visit
- prediction
- psychological correlates
- Recruitment method
- reliability analysis
- Remote meetings
- Response burden
- review
- routines
- self-training
- sensing
- Sentiment Analysis
- shape classification
- Shape descriptor
- shape recognition
- Shape retrieval
- shot boundary detection
- sketch
- small group interactions
- Smartphone application
- smartphone data
- smartphone sensing
- Smartphones
- Snack and Meal
- social computing
- social context
- social media
- social networks
- social psychology
- Social video
- sparse autoencoder
- sparse coding
- spatial data
- spectral shot clustering
- Speech activity
- Standard drink
- stress
- support
- survey
- Task-competence
- telemonitoring
- Text classification
- thin slices
- transfer learning
- Ubiquitous Computing
- unsupervised methods
- urban awareness
- Urban Computing
- Urban Crowdsourcing
- usability
- user aggregated behavior
- user behavior
- user modeling
- user satisfaction
- user study
- verbal analysis
- Verbal content
- video
- Video annotation
- video resumes
- video structuring
- video-sharing
- Visual similarity
- vlog
- vlogging
- vlogs
- wearable sensing
- well being
- well-being
- young adults
- Youth
- youtube
- YouTubeYouTube
Publications of Daniel Gatica-Perez sorted by first author
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| How to Tell Ancient Signs Apart? Recognizing and Visualizing Maya Glyphs with CNNs, , and , in: ACM Journal on Computing and Cultural Heritage (JOCCH), 11(4):20, 2018 |
[DOI] |
| Maya Codical Glyph Segmentation: A Crowdsourcing Approach, , and , Idiap-RR-01-2017 |
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| Shape Representations for Maya Codical Glyphs: Knowledge-driven or Deep?, , and , in: 15th International Workshop on Content-Based Multimedia Indexing, 2017 |
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| Visual Analysis of Maya Glyphs via Crowdsourcing and Deep Learning, , École Polytechnique Fédérale de Lausanne, 2017 |
[DOI] |
| Evaluating Shape Representations for Maya Glyph Classification, , and , in: ACM Journal on Computing and Cultural Heritage (JOCCH), 9(3), 2016 |
| Is That a Jaguar? Segmenting Ancient Maya Glyphs via Crowdsourcing, , and , in: Proc. ACM Int. Workshop on Crowdsourcing for Multimedia, Orlando, pages 37-40, ACM New York, 2014 |
[DOI] |
| Ancient Maya Writings as High-Dimensional Data: a Visualization Approach, , , and , in: Digital Humanities (DH), Krakow, 2016 |
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| The Workshop on Computational Personality Recognition 2014, , , , , and , in: Proceedings of the ACM International Conference on Multimedia, 2014 |
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| Rapport with Virtual Agents: What do Human Social Cues and Personality Explain?, , and , in: IEEE Transactions on Affective Computing, 8(3):382-395, 2017 |
[DOI] |
| How Do You Like Your Virtual Agent?: Human-Agent Interaction Experience through Nonverbal Features and Personality Traits, , and , in: Human Behavior Understanding, pages 1-15, Springer, 2014 |
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| International Conference on Mobile and Ubiquitous Multimedia, , and , in: Happy and Agreeable? Multi-Label Classification of Impressions in Social Video, Linz, Austria, pages 109-120, ACM, 2015 |
[DOI] [URL] |
| Exploiting observers' judgements for nonverbal group interaction analysis, , and , in: IEEE Conference on Automatic Face and Gesture Recognition, pages 6, IEEE, 2011 |
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| Inferring truth from multiple annotators for social interaction analysis, , and , in: Neural Information Processing Systems (NIPS) Workshop on Modeling Human Communication Dynamics (HCD), pages 4, 2011 |
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| Who's Who with Big-Five: Analyzing and Classifying Personality Traits with Smartphones, , and , in: International Symposium on Wearable Computing, pages 8, 2011 |
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| Mining Large-Scale Smartphone Data for Personality Studies, , and , in: Personal and Ubiquitous Computing, 2012 |
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D
| Professional YouTubers’ health videos as research material: Formulating a multi-method design in health psychology, , , , and , in: Methods in Psychology, Special Issue on Innovations in Qualitative Research, 5, 2021 |
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| Smartphone usage in the wild: a large-scale analysis of applications and context, , and , in: 13th International Conference on Multimodal Interaction, 2011 |
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| A Probabilistic Kernel Method for Human Mobility Prediction with Smartphones, , , and , in: Pervasive and Mobile Computing, 2014 |
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| The Places of Our Lives: Visiting Patterns and Automatic Labeling from Longitudinal Smartphone Data, and , in: IEEE Transactions on Mobile Computing, 2013 |
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| Where and What: Using Smartphones to Predict Next Locations and Applications in Daily Life, and , in: Pervasive and Mobile Computing, 2013 |
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| Contextual Conditional Models for Smartphone-based Human Mobility Prediction, and , in: Proceedings of the 14th ACM International Conference on Ubiquitous Computing, 2012 |
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| Contextual grouping: discovering real-life interaction types from longitudinal Bluetooth data, and , in: 12th International Conference on Mobile Data Management, 2011 |
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| GroupUs: Smartphone Proximity Data and Human Interaction Type Mining, and , in: 15th annual International Symposium on Wearable Computers, San Francisco, USA, 2011 |
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| By their apps you shall understand them: mining large-scale patterns of mobile phone usage, and , in: The 9th International Conference on Mobile and Ubiquitous Multimedia, 2010 |
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| Human Interaction Discovery in Smartphone Proximity Networks, and , in: Personal and Ubiquitous Computing, 2012 |
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| Inferring social activities with mobile sensor networks, , , , and , in: 15th ACM International Conference on Multimodal Interaction, 2013 |
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| Extracting Mobile Behavioral Patterns with the Distant N-Gram Topic Model, and , in: Proceedings of the IEEE International Symposium on Wearable Computers, Newcastle, 2012 |
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| A Probabilistic Approach to Mining Mobile Phone Data Sequences, and , in: Personal and Ubiquitous Computing, 2012 |
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| Discovering Routines from Large-Scale Human Locations using Probabilistic Topic Models, and , in: ACM Transactions on Intelligent Systems and Technology, 2(1), 2011 |
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| Probabilistic Mining of Socio-Geographic Routines from Mobile Phone Data, and , in: IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 4(4), 2010 |
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| Mining Human Location-Routines using a Multi-Level Topic Model, and , Idiap-RR-28-2010 |
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| Mining Human Location-Routines Using a Multi-Level Approach to Topic Modeling, and , in: 2010 IEEE Second International Conference on Social Computing, SIN Symposium, Minneapolis, Minnesota, USA, 2010 |
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| Learning and Predicting Multimodal Daily Life Patterns from Cell Phones, and , in: ICMI-MLMI, 2009 |
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