10th IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition. May 13-15, 2015 Beijing, China

Transcription

1 10th IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition May 13-15, 2015 Beijing, China

2 Sponsored by:

3 Welcome Message Welcome to the 10th IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition (GbR2015) in Beijing, China, 2015! The series of GbR Workshop is sponsored by the TC15 (Graph-based Representations) of IAPR (International Association for Pattern Recognition), started from The GbR2015 follows the editions of 1997 in Lyon (France), 1999 in Castle of Haindorf (Austria), 2001 in Ischia (Italy), 2003 in York (UK), 2005 in Poitiers (France), 2007 in Alicante (Spain), 2009 in Venice (Italy), 2011 in Münster (Germany), and 2013 in Vienna (Austria). Graph is a very effective structure for representing structural patterns and has been widely used in pattern recognition, computer vision, machine learning, and data mining. Structural pattern recognition methods usually represent a pattern as a graph modeling the primitives and their interrelationship. A digital image can be viewed as a graph with its pixels as nodes. Many machine learning methods view sample points as the nodes of a graph for modeling their affinity. Social media and biological data are often represented as graphs or networks. Theory and methods of graph data analysis have been studied intensively for graph generation, matching, labeling, segmentation, clustering, classification, and data mining in various fields. The GbR Workshop encourages all related works from such fields. The GbR2015 received 53 full submissions. The authors are from Asia, Europe, America, and Oceania. Each submission was assigned to three Program Committee (PC) members for review, and 11 sub-reviewers were invited by the PC members. Based on the reviews, 36 papers were accepted for presentation at the workshop and inclusion in the proceedings. The accepted papers cover diverse issues of graph-based methods and applications, with 7 in graph representation, 15 in graph matching, 7 in graph clustering and classification, and 7 in graph-based applications. In addition to regular presentations, we invited two established researchers to present keynote speeches. Professor Marcello Pelillo of University of Venice (Italy) and Dr. Xing Xie of Microsoft Research Asia (Beijing, China) will present speeches titled Revealing Structure in Large Graphs: Szemerdi s Regularity Lemma and Its Use in Pattern Recognition and Understanding Users by Connecting Large Scale Social Graphs, respectively. We are grateful to the invited speakers, the authors of all submitted papers, the Program Committee members, and reviewers, and the staff of the Organizing Committee. Without their contributions, this workshop would not have been a success. We also thank Springer for publishing the proceedings, especially Mr. Alfred Hofmann and Ms. Anna Kramer for their efforts and patience in collecting and editing the proceedings. We welcome you to take part in this academic event and hope you find GbR2015 an enjoyable and fruitful workshop. May 2015 Cheng-Lin Liu Bin Luo Walter G. Kropatsch Jian Cheng 1

4 Organizing Committee Sponsors National Laboratory of Pattern Recognition, Institute of Automation of CAS IAPR TC-15 Program Co-Chairs Cheng-Lin Liu Bin Luo Walter G. Kropatsch Institute of Automation of CAS, China Anhui University, China Vienna University of Technology, Austria Technical Program Committee: Xiang Bai Xiao Bai Roberto M. Cesar Badong Chen Jian Cheng Ananda Chowdhury Donatello Conte Guillaume Damiand Francisco Escolano Volkmar Frinken Pasquale Foggia Edwin R. Hancock Qiang Ji Xiaoyi Jiang Walter G. Kropatsch Cheng-Lin Liu Zhiyong Liu Josep Lladós Bin Luo Jean-Marc Ogier Shinichiro Omachi Marcello Pelillo Peng Ren Kaspar Riesen Huazhong University of Science and Technology, China Beihang University, China University of São Paulo, Brazil Xi an Jiaotong University, China Institute of Automation of CAS, China Jadavpur University, India Université Francois-Rabelais, Tours, France LIRIS laboratory, France Universidad de Alicante, Spain Kyushu University, Japan University of Salerno, Italy University of York, UK Rensselaer Polytechnic Institute, USA University of Münster, Germany Vienna University of Technology, Austria Institute of Automation of CAS, China Institute of Automation of CAS, China Universitat Autònoma de Barcelona, Spain Anhui University, China Université de La Rochelle, France Tohoku University, Japan University of Venice, Italy China University of Petroleum, China University of Applied Sciences and Arts, Switzerland 2

5 Francesc Serratosa Ali Shokoufandeh Andrea Torsello Seiichi Uchida Mario Vento Richard Wilson Shuicheng Yan Changshui Zhang Universitat Rovira i Virgili, Spain Drexel University, USA Ca Foscari University of Venice, Italy Kyushu University, Japan University of Salerno, Italy University of York, UK National University of Singapore, Singapore Tsinghua University, China Local Organizing Committee: Jian Cheng Yan-Ming Zhang Ming Li Institute of Automation of CAS, China Institute of Automation of CAS, China Institute of Automation of CAS, China Referees Xiang Bai Xiao Bai Luc Brun Roberto M. Cesar Badong Chen Jian Cheng Ananda Chowdhury Donatello Conte Guillaume Damiand Francisco Escolano Pasquale Foggia Volkmar Frinken Edwin R. Hancock Qiang Ji Xiaoyi Jiang Josep Llados Cheng-Lin Liu Zhi-Yong Liu Bin Luo Jean-Marc Ogier Shinichiro Omachi Marcello Pelillo Peng Ren Kaspar Riesen Francesc Serratosa Ali Shokoufandeh Andrea Torsello Mario Vento Seiichi Uchida Richard Wilson Shuicheng Yan Changshui Zhang Additional Referees Li Chuan Andreas Fischer Llus-Pere De Las Heras Yinlin Li Xiaodan Liang Muhammad Muzzamil Luqman Tomo Miyazaki Alessia Saggese XinggangWang Xu Yang Suiwu Zheng 3

6 Program at a Glance May 13 (Wednesday) May 14 (Thursday) May 15 (Friday) 8:00-9:00 Registration 9:00-9:20 Opening 9:20-10:20 Keynote Speech 1 10:20-10:50 Tea Break 10:50-12:30 Graph Matching 1 12:30-14:00 Lunch 14:00-15:40 Graph-based Representation 1 15:40-16:10 Tea Break 16:10-17:50 Graph Clustering and Classification 1 9:00-10:00 Keynote Speech 2 10:00-10:30 Tea Break 10:30-12:35 Graph-based Applications 1 12:35-14:00 Lunch 14:00-15:40 Graph Matching 2 15:40-16:10 Tea Break 16:10-17:25 Graph Clustering and Classification 2 17:25-18:10 TC15 Session 19:30-22:00 Banquet 8:40-10:20 Graph Matching 3 10:20-10:50 Tea Break 10:50-12:30 Graph-based Representation 2 12:30-14:00 Lunch 14:00-15:40 Graph-based Applications 2 15:40-16:00 Closing 4

7 Keynote Speech 1 Revealing Structure in Large Graphs: Szemerédi's Regularity Lemma and Its Use in Pattern Recognition Abstract: Introduced in the mid-1970's as an intermediate step in proving a long-standing conjecture on arithmetic progressions, Szemeredi's regularity lemma has emerged over time as a fundamental tool in different branches of discrete mathematics and theoretical computer science. Roughly, it states that every graph can be approximated by the union of a small number of random-like bipartite graphs called regular pairs. In other words, the result provides us a way to obtain a good description of a large graph using a small amount of data, and can be regarded as a manifestation of the all-pervading dichotomy between structure and randomness. In this talk, I will provide an overview of the regularity lemma and variations thereof and will discuss its relevance in the context of structural pattern recognition. Biography: Marcello Pellilo is Full Professor of Computer Science at Ca Foscari University in Venice, Italy, where he leads the Computer Vision and Pattern Recognition group. He held visiting research positions at Yale University, McGill University, the University of Vienna, York University (UK), the University College London, and the National ICT Australia (NICTA). He has published more than 150 technical papers in refereed journals, handbooks, and conference proceedings in the areas of pattern recognition, computer vision and machine learning. He is General Chair for ICCV 2017 and has served as Program Chair for several conferences and workshops (EMMCVPR, SIMBAD, S+SSPR, etc.). He serves (has served) on the Editorial Boards of the journals IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Pattern Recognition, IET Computer Vision, Frontiers in Computer Image Analysis, Brain Informatics, and serves on the Advisory Board of the International Journal of Machine Learning and Cybernetics. Prof. Pelillo is a Fellow of the IEEE and a Fellow of the IAPR. His Erdös number is 2. 5

8 Keynote Speech 2 Understanding Users by Connecting Large Scale Social Graphs Abstract: With the rapid development of positioning, sensor and smart device technologies, large quantities of human behavioral data are now readily available. They reflect various aspects of human mobility and activities in the physical world. The availability of this data presents an unprecedented opportunity to gain a more in depth understanding of users and provide them with personalized online experience while respecting their privacy. In this talk, I will describe a vision toward building a unified user knowledge graph supplemented with knowledge generated from both online and offline user data, such as social posts, check-in trajectories, and mobile communication histories. We proposed a graph node similarity measurement in consideration with both graph structure and descriptive information, and a graph linking/de-anonymization algorithm based on the measurement. The algorithm has been evaluated in social graphs with thousands of nodes from Microsoft Academic Search, LiveJournal, and the Enron dataset, and a social graph with millions of nodes from Tencent Weibo. Then I will present LifeSpec, a computational framework for exploring and hierarchically categorizing urban lifestyles, based on large scale publicly available heterogeneous behavioral data from multiple social networks. Biography: Xing Xie is currently a senior researcher in Microsoft Research Asia, and a guest Ph.D. advisor for the University of Science and Technology of China. He received his B.S. and Ph.D. degrees in Computer Science from the University of Science and Technology of China in 1996 and 2001, respectively. He joined Microsoft Research Asia in July 2001, working on spatial data mining, location based services, social networks and ubiquitous computing. During the past years, he has published over 140 referred journal and conference papers. He has more than 50 patents filed or granted. He currently serves on the editorial boards of ACM Transactions on Intelligent Systems and Technology, Springer GeoInformatica, Elsevier Pervasive and Mobile Computing, Journal of Location Based Services, and Communications of the China Computer Federation. He has worked as a guest editor of IEEE Transactions on Multimedia and IEEE Intelligent Systems. In recent years, he was involved in the program or organizing committees of over 70 conferences and workshops. Especially, he initiated the LBSN workshop series and served as program co-chair of ACM UbiComp 2011 and program chair of the 8th Chinese Pervasive Computing Conference. In Oct. 2009, he founded the SIGSPATIAL China chapter which was the first regional chapter of ACM SIGSPATIAL. He is a member of Joint Steering Committee of the UbiComp and Pervasive Conference Series. He is a senior member of ACM, the IEEE, and China Computer Federation. 6

9 Technical Program May 13 (Wednesday) Session, Title, Author Page # in Proceedings 8:00-9:00 Registration 9:00-9:20 Opening 9:20-10:20 Keynote Speech 1, Chair: Bin Luo 10:20-10:50 Break, Group Photo Revealing Structure in Large Graphs: Szemerédi's Regularity Lemma and Its Use in Pattern Recognition Marcello Pelillo (University of Venice, Italy) 10:50-12:30 Graph Matching 1, Chair: Andreas Fisher 12:30-14:00 Lunch A First Step Towards Exact Graph Edit Distance Using Bipartite Graph Matching Miquel Ferrer, Francesc Serratosa and Kaspar Riesen Consensus of Two Graph Correspondences through a Generalisation of the Bipartite Graph Matching Algorithm Carlos Francisco Moreno-García, Francesc Serratosa and Xavier Cortés Revisiting Volegnant-Jonker for Approximating Graph Edit Distance William Jones, Aziem Chawdhary and Andy King A Hypergraph Matching Framework for Refining Multi-source Feature Correspondences He Zhang, Bin Du, Yanjiang Wang and Peng Ren 14:00-15:40 Graph-based Representation 1, Chair: Nean-Marc Ogier 15:40-16:10 Break Approximation of Graph Edit Distance in Quadratic Time Kaspar Riesen, Miquel Ferrer, Andreas Fischer and Horst Bunke Data Graph Formulation as the Minimum-Weight Maximum-Entropy Problem Samuel de Sousa and Walter Kropatsch Thermodynamics of Time Evolving Networks Cheng Ye, Andrea Torsello, Richard C. Wilson and Edwin R. Hancock A Subpath Kernel for Learning Hierarchical Image Representations Yanwei Cui, Laetitia Chapel and Sébastien Lefèvre

10 16:10-17:50 Graph Clustering and Classification 1, Chair: Peng Ren On the Influence of Node Centralities on Graph Edit Distance for Graph Classification Xavier Cortés, Francesc Serratosa and Carlos F. Moreno-García A Mixed Weisfeiler-Lehman Graph Kernel Lixiang Xu, Jin Xie, Xiaofeng Wang and Bin Luo A Quantum Jensen-Shannon Graph Kernel using Discrete-time Quantum Walks Lu Bai, Luca Rossi, Peng Ren, Zhihong Zhang and Edwin R. Hancock Density Based Cluster Extension and Dominant Sets Clustering Jian Hou, Chunshi Sha, Xu E, Qi Xia and Naiming Qi May 14 (Thursday) 9:00-10:00 Keynote Speech 2, Chair: Walter Kropatsch 10:00-10:30 Break Understanding Users by Connecting Large Scale Social Graphs Xing Xie (Microsoft Research Asia, China) 10:30-12:35 Graph-based Applications 1, Chair: Francesc Serratosa 12:30-14:00 Lunch Report on the First Contest on Graph Matching Algorithms for Pattern Search in Biological Databases Vincenzo Carletti, Pasquale Foggia, Mario Vento and Xiaoyi Jiang Kite Recognition by means of Graph Matching Kamel Madi, Hamida Seba, Hamamache Kheddouci, Charles-Edmond Bichot, Olivier Barge, Christine Chataigner, Remy Crassard, Emmanuelle Regagnon and Emmanuelle Vila From bags to graphs of stereo subgraphs in order to predict molecule's properties Pierre-Anthony Grenier, Luc Brun and Didier Villemin An Entropic Edge Assortativity Measure Cheng Ye, Richard C. Wilson and Edwin R. Hancock Graph Based Lymphatic Vessel Wall Localisation and Tracking Ehab Essa, Xianghua Xie and Jonathan Jones 14:00-15:40 Graph Matching 2, Chair: Luc Brun

11 GEM++: a tool for solving substitution-tolerant subgraph isomorphism Julien Lerouge, Pierre Le Bodic, Pierre Héroux and Sébastien Adam A Graph Database Repository and Performance Evaluation Metrics for Graph Edit Distance Zeina Abu-Aisheh, Romain Raveaux and Jean-Yves Ramel Improving Hausdorff Edit Distance Using Structural Node Context Andreas Fischer, Seiichi Uchida, Volkmar Frinken, Kaspar Riesen and Horst Bunke VF2 Plus: An Improved Version of VF2 for Biological Graphs Vincenzo Carletti, Pasquale Foggia, and Mario Vento :40-16:10 Break 16:10-17:25 Graph Clustering and Classification 2, Chair: Jian Cheng Salient Object Segmentation from Stereoscopic Images Xingxing Fan, Zhi Liu and Linwei Ye Causal Video Segmentation using Superseeds and Graph Matching Vijay N. Gangapure, Susmit Nanda, Ananda S. Chowdhury and Xiaoyi Jiang Fast Minimum Spanning Tree based Clustering Algorithms on Local Neighborhood Graph R.Jothi, Sraban Kumar Mohanty and Aparajita Ojha 17:25-18:10 TC15 session, Chair: Xiaoyi Jiang 19:30-22:00 Banquet May 15 (Friday) 8:40-10:20 Graph Matching 3, Chair: Pasquale Foggia Approximate Graph Edit Distance Computation Combining Bipartite Matching and Exact Neighborhood Substructure Distance Vincenzo Carletti, Benoit Gaüzère, Luc Brun and Mario Vento Multi-layer Tree Matching Using HSTs Yusuf Osmanlioglu and Ali Shokoufandeh Large-scale Graph Indexing using Binary Embeddings of Node Contexts Pau Riba, Josep Llados, Alicia Fornes and Anjan Dutta Attributed Relational Graph Matching with Sparse Relaxation and Bistochastic Normalization Bo Jiang, Jin Tang and Bin Luo

12 10:20-10:50 Break 10:50-12:30 Graph-based Representation 2, Chair: Xiao Bai 12:30-14:00 Lunch Coupled-Feature Hypergraph Representation for Feature Selection Zhihong Zhang, Jianbing Xiahou, Lu Bai and Edwin R. Hancock Reeb Graphs Through Local Binary Patterns Ines Janusch and Walter Kropatsch Incremental embedding within a dissimilarity-based framework Rachid Hafiane, Luc Brun and Salvatore Tabbone Learning Graph Model for Different Dimensions Image Matching Haoyi Zhou, Xiao Bai, Jun Zhou, Haichuan Yang and Yun Liu 14:00-15:40 Graph-based Applications 2, Chair: Josep Llados 15:40-16:00 Closing Skeletal Graphs from Schrodinger Magnitude and Phase Francisco Escolano, Edwin R. Hancock and Miguel Angel Lozano Isometric Mapping Hashing Yanzhen Liu, Xiao Bai, Haichuan Yang, Jun Zhou and Zhihong Zhang A Comic Retrieval System Based on Multilayer Graph Representation and Graph Mining Thanh-Nam Le, Muhammad Muzzamil Luqman,Jean-Christophe Burie, and Jean-Marc Ogier Learning High-Order Structures for Texture Retrieval Ni Liu, Georgy Gimelfarb and Patrice Delmas

13 Workshop Venue The meeting room is on the 3rd floor of Intelligence Building (map below), Meeting Room #1 ( 智能化大厦 3 层第一会议室 ). You should enter the campus of CASIA through the north gate of Automation Building ( 自动化大厦 ), and then enter the Intelligence Building Intelligence Building 11

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