Track 1: Pattern Recognition and Machine Learning

Prof. Edwin Hancock (University of York, UK)
Prof. Enrique Sucar (INAOE, Puebla, México )
Prof. Lian Wang (National Lab of Pattern Recognition, China)

• Statistical, syntactic and structural pattern recognition

• Machine learning and data mining

• Artificial neural networks

• Dimensionality reduction and manifold learning

• Classification and clustering

• Graphical Models for Pattern Recognition

• Representation and analysis in pixel/voxel images

• Support vector machines and kernel methods

• Symbolic learning

• Active and ensemble learning

• Deep learning

• Pattern recognition for big data

• Transfer learning

• Semi-supervised learning and spectral methods

• Model selection

• Reinforcement learning and temporal models

• Performance Evaluation

Track 2: Computer Vision and Robot Vision

Prof. Richard Hartley (Australian National University, Australia)
Prof. Anders Heyden (University, Lund, Sweden)
Prof. Ales Leonardis (University of Birmingham, UK)
Prof. Sudeep Sarkar (University of South Florida, USA)

• Vision sensors

• Early/low-level vision

• Biologically motivated vision

• Illumination and reflectance modeling

• Image based modeling

• Physics-based vision

• Perceptual organization

• Shape modeling and encoding

• Computational photography

• 3D shape recovery

• Motion, tracking and video analysis

• 3D sensors: depth sensors, ToF, Kinect

• 2D/3D object detection and recognition

• Activity and event analysis

• Scene understanding

• Occlusion and shadow detection

• Stereo and multiple view geometry

• Reconstruction and camera motion estimation

• Vision for graphics

• Deep learning

• Vision for robotics

• Cognitive and embodied visión

• Humanoid vision

Track 3: Image, Speech, Signal and Video Processing

Prof. Michael Felsberg (University of Linköping, Sweden)
Prof. Vaclav Hlavac (Czech Technical University, Czech Republic)
Prof. Dong Xu (Nanyang Technological University, Singapore)

• Image, Speech, Signal and Video Processing

• Image and video analysis and understanding

• Sensor array & multichannel signal processing

• Segmentation, features and descriptors

• Texture and color analysis

• Enhancement, restoration and filtering

• Coding, compression and super-resolution

• Facial expression recognition

• Affective computing

• Human computer interaction

• Human body motion and gesture based interaction

• Audio and acoustic processing and analysis

• Automatic speech and speaker recognition

• Spoken language processing

• Speech and natural language based interaction

• Group interaction: analysis of verbal and non-verbal communication

• Multimedia analysis, indexing and retrieval

• Depth & range sensor data processing and analysis

Track 4: Document Analysis, Biometrics and Pattern Recognition Applications

Prof. Anil Jain (Michigan State University, USA)
Prof. Mark Nixon (University of Southampton, UK)
Prof. Tieniu Tan (Chinese Academy of Sciences, China)
Dr. Luc Vincent (Google, USA)

• Character and Text Recognition

• Handwriting Recognition

• Graphics Recognition

• Document Understanding

• Gesture and Behavior Analysis

• Mixed and Augmented Reality

• Face, fingerprint and iris recognition

• Other biometrics (gait, soft, speaker, periocular, etc.)

• Novel biometrics

• Biometric systems and applications

• Multi-biometrics

• Forensic biometrics and applications

• Bioinformatics

• Surveillance and Security

• Search, Retrieval and Visualization

• Art, Cultural Heritage and Entertainment

• Industrial image analysis

• Human computer interaction

• Analysis of humans

• Pattern and digital evidence

• Performance analysis and enhancement

• Applications of pattern recognition to big data

Track 5: Biomedical Image Analysis and Applications

Prof. Xiaoyi Jiang (University of Münster, Germany)
Prof. Ioannis Kakadiaris (University of Houston, USA)
Prof. Reinhard Klette (Auckland University of Technology, NZ)

• Medical image and signal analysis

• Biological image and signal analysis

• Modeling, simulation and visualization

• Computer-aided detection and diagnosis

• Image guidance and robot guidance of interventions

• Content based image retrieval and data mining

• Medical and biological imaging

• Segmentation of biomedical images

• Molecular and cellular image analysis

• Volumetric image analysis

• Deformable object tracking and registration

• Computational anatomy and digital human

• VR/AR in medical education, diagnosis and surgery

• Medical robotics

• Imaging and hardware for health care

• Brain-computer interfaces

• Data mining for biological databases

• Algorithms for molecular biology

• Deep learning for biomedical image analysis