Understanding the Emotional Impact of Images Jia JIA Computer Science, Tsinghua University Joint work with Xiaohui WANG, Peiyun HU, Sen WU, Jie TANG and.

Slides:



Advertisements
Similar presentations
1 Cross-domain Collaboration Recommendation Jie Tang 1, Sen Wu 1, Jimeng Sun 2, Hang Su 1 1 Tsinghua University 2 IBM TJ Watson Research Center.
Advertisements

1 From Sentiment to Emotion Analysis in Social Networks Jie Tang Department of Computer Science and Technology Tsinghua University, China.
Active Learning for Streaming Networked Data Zhilin Yang, Jie Tang, Yutao Zhang Computer Science Department, Tsinghua University.
Confluence: Conformity Influence in Large Social Networks
Predicting Tie Strength with the Facebook API Tasos Spiliotopoulos Madeira-ITI, University of Madeira, Portugal / Harokopio University, Greece Diogo Pereira.
1 Social Influence Analysis in Large-scale Networks Jie Tang 1, Jimeng Sun 2, Chi Wang 1, and Zi Yang 1 1 Dept. of Computer Science and Technology Tsinghua.
IJCAI Wei Zhang, 1 Xiangyang Xue, 2 Jianping Fan, 1 Xiaojing Huang, 1 Bin Wu, 1 Mingjie Liu 1 Fudan University, China; 2 UNCC, USA {weizh,
Presented by Arshad Jamal, Rajesh Dhania, Vinkal Vishnoi Active hashing and its application to image and text retrieval Yi Zhen, Dit-Yan Yeung, Published.
1 Yuxiao Dong *$, Jie Tang $, Sen Wu $, Jilei Tian # Nitesh V. Chawla *, Jinghai Rao #, Huanhuan Cao # Link Prediction and Recommendation across Multiple.
Graph Data Management Lab School of Computer Science , Bristol, UK.
Relational Learning with Gaussian Processes By Wei Chu, Vikas Sindhwani, Zoubin Ghahramani, S.Sathiya Keerthi (Columbia, Chicago, Cambridge, Yahoo!) Presented.
1 1 Chenhao Tan, 1 Jie Tang, 2 Jimeng Sun, 3 Quan Lin, 4 Fengjiao Wang 1 Department of Computer Science and Technology, Tsinghua University, China 2 IBM.
Statistical Models for Networks and Text Jimmy Foulds UCI Computer Science PhD Student Advisor: Padhraic Smyth.
Graph Based Semi- Supervised Learning Fei Wang Department of Statistical Science Cornell University.
WORD-PREDICTION AS A TOOL TO EVALUATE LOW-LEVEL VISION PROCESSES Prasad Gabbur, Kobus Barnard University of Arizona.
Jinhui Tang †, Shuicheng Yan †, Richang Hong †, Guo-Jun Qi ‡, Tat-Seng Chua † † National University of Singapore ‡ University of Illinois at Urbana-Champaign.
 To play ARIS games, download the ARIS client from the app store on an iOS device and create a player account (if you are using an iPad, look for ARIS.
1 1 Chenhao Tan, 1 Jie Tang, 2 Jimeng Sun, 3 Quan Lin, 4 Fengjiao Wang 1 Department of Computer Science and Technology, Tsinghua University, China 2 IBM.
Active Learning for Networked Data Based on Non-progressive Diffusion Model Zhilin Yang, Jie Tang, Bin Xu, Chunxiao Xing Dept. of Computer Science and.
UNIVERSITY of NOTRE DAME COLLEGE of ENGINEERING Preserving Location Privacy on the Release of Large-scale Mobility Data Xueheng Hu, Aaron D. Striegel Department.
School of Information Technology & Electrical Engineering Multiple Feature Hashing for Real-time Large Scale Near-duplicate Video Retrieval Jingkuan Song*,
Yu-Gang Jiang, Yanran Wang, Rui Feng Xiangyang Xue, Yingbin Zheng, Hanfang Yang Understanding and Predicting Interestingness of Videos Fudan University,
1 From Sentiment to Emotion Analysis in Social Networks Jie Tang Department of Computer Science and Technology Tsinghua University, China.
End-to-End Text Recognition with Convolutional Neural Networks
Science Problem: Cognitive capacity (human/scientist understanding), storage and I/O have not kept up with our capacity to generate massive amounts physics-based.
Zhenbao Liu 1, Shaoguang Cheng 1, Shuhui Bu 1, Ke Li 2 1 Northwest Polytechnical University, Xi’an, China. 2 Information Engineering University, Zhengzhou,
Beauty is Here! Evaluating Aesthetics in Videos Using Multimodal Features and Free Training Data Yanran Wang, Qi Dai, Rui Feng, Yu-Gang Jiang School of.
IPad Apps for Teachers. Free Books Over 23,000 free books to read!
Exploit of Online Social Networks with Community-Based Graph Semi-Supervised Learning Mingzhen Mo and Irwin King Department of Computer Science and Engineering.
Probabilistic Models for Discovering E-Communities Ding Zhou, Eren Manavoglu, Jia Li, C. Lee Giles, Hongyuan Zha The Pennsylvania State University WWW.
Dual Transfer Learning Mingsheng Long 1,2, Jianmin Wang 2, Guiguang Ding 2 Wei Cheng, Xiang Zhang, and Wei Wang 1 Department of Computer Science and Technology.
A New Method for Automatic Clothing Tagging Utilizing Image-Click-Ads Introduction Conclusion Can We Do Better to Reduce Workload?
MyON reader Provide access to a growing collection of enhanced digital books. Connects student interests and reading levels to personalize reading. Monitor.
CoNMF: Exploiting User Comments for Clustering Web2.0 Items Presenter: He Xiangnan 28 June School of Computing National.
Image Classification over Visual Tree Jianping Fan Dept of Computer Science UNC-Charlotte, NC
1 From Sentiment to Emotion Analysis in Social Networks Jie Tang Department of Computer Science and Technology Tsinghua University, China.
Towards Total Scene Understanding: Classification, Annotation and Segmentation in an Automatic Framework N 工科所 錢雅馨 2011/01/16 Li-Jia Li, Richard.
Change Blindness Images Li-Qian Ma 1, Kun Xu 1, Tien-Tsin Wong 2, Bi-Ye Jiang 1, Shi-Min Hu 1 1 Tsinghua University 2 The Chinese University of Hong Kong.
Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology 1 Mining Advisor-Advisee Relationships from Research Publication.
Observation vs. Inferences The Local Environment.
Personality Classification: Computational Intelligence in Psychology and Social Networks A. Kartelj, School of Mathematics, Belgrade V. Filipovic, School.
A Connectivity-Based Popularity Prediction Approach for Social Networks Huangmao Quan, Ana Milicic, Slobodan Vucetic, and Jie Wu Department of Computer.
Hierarchical Motion Evolution for Action Recognition Authors: Hongsong Wang, Wei Wang, Liang Wang Center for Research on Intelligent Perception and Computing,
Facial Smile Detection Based on Deep Learning Features Authors: Kaihao Zhang, Yongzhen Huang, Hong Wu and Liang Wang Center for Research on Intelligent.
Understanding and Predicting Image Memorability at a Large Scale A. Khosla, A. S. Raju, A. Torralba and A. Oliva International Conference on Computer Vision.
3D ShapeNets: A Deep Representation for Volumetric Shapes Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, Jianxiong Xiao.
Modeling Perspective Effects in Photographic Composition Zihan Zhou, Siqiong He, Jia Li, and James Z. Wang The Pennsylvania State University.
1 Social Influence and Sentiment Analysis —From Sentiment to Emotion Analysis in Social Networks Jie Tang Department of Computer Science and Technology.
Multi-Modal Bayesian Embeddings for Learning Social Knowledge Graphs Zhilin Yang 12, Jie Tang 1, William W. Cohen 2 1 Tsinghua University 2 Carnegie Mellon.
GST Helpline - A Complete GST App TO RESOLVE GST INDIA QUERIES
Fig. 4 Careers and their Q parameter.
Mining User Similarity from Semantic Trajectories
CNN-RNN: A Unified Framework for Multi-label Image Classification
Inference as a Feedforward Network
Social Role-Aware Emotion Contagion in Image Social Networks
Learning to Detect a Salient Object
Cheng-Ming Huang, Wen-Hung Liao Department of Computer Science
Example: Academic Search
دانشگاه شهیدرجایی تهران
تعهدات مشتری در کنوانسیون بیع بین المللی
Department of Computer Science University of York
MEgo2Vec: Embedding Matched Ego Networks for User Alignment Across Social Networks Jing Zhang+, Bo Chen+, Xianming Wang+, Fengmei Jin+, Hong Chen+, Cuiping.
Y2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences 1, Zhizhong.
Example: Academic Search
边缘检测年度进展概述 Ming-Ming Cheng Media Computing Lab, Nankai University
Heterogeneous convolutional neural networks for visual recognition
Multi-Modal Multi-Scale Deep Learning for Large-Scale Image Annotation
Week 1 Overview - Cecilia La Place
A, Selected 4 quantitative imaging features significantly associated with 3 imaging subtypes, including tumor volume, tumor sphericity, tumor homogeneity.
Presentation transcript:

Understanding the Emotional Impact of Images Jia JIA Computer Science, Tsinghua University Joint work with Xiaohui WANG, Peiyun HU, Sen WU, Jie TANG and Lianhong CAI

 Framework: Images -Aesthetic Effects -Emotions  Model: Factor Graphs for images in Social Networks

App1: Emotion Distribution on Flickr Before Thanksgiving 2011 VS During Thanksgiving holiday Happy, Cheerful, and Peaceful 100,000 Images from Flickr

App2: Modify Images with Emotional Words Happy Natural Clear Original Image Summe r? Autum n? Winter? More than 180 different effects

“Emotion Modifier” Welcome to download from iTunes Store!

Thank you for your attention! Any Question? APP for iPad (support IOS 5.x ) : Emotion Modifier. Free Download! From

Modeling Emotions via Aesthetic Effects How to characterize levels of emotional impact? We propose a novel notion of using aesthetic effects (quantified in image-scale space) as an intermediate layer to model the high level emotional semantics of images. Middle Level High Level

What affective model to predict the emotional impact?  Large-scale Dataset: 100,000 images in social networks with comments as emotional tag.  Model: semi-supervised factor graph model to incorporate color- based features, aesthetic effect, social features and emotional impact. Jie Tang, et al., Learning to Infer Social Ties in Large Networks. In proceeding of ECML-PKDD 2011 Modeling Social Network via Factor Graphs

Feedback: Privacy Policy Feedback
Do Not Sell My Personal Information
About project: SlidePlayer Terms of Service

© 2024 SlidePlayer.com Inc. All rights reserved.