| Type | Early Registration (Until 06/10/2017) | After (06/10/2017) |
|---|---|---|
| Professional | R$ 500,00 | R$ 700,00 |
| SBC Professional | R$ 425,00 | R$ 595,00 |
| Graduate Student | R$ 250,00 | R$ 350,00 |
| SBC Graduate Student | R$ 210,00 | R$ 295,00 |
| Undergrad. Student | R$ 60,00 | |
| SBC Undergrad. Student | R$ 50,00 |
John Tsotsos is Distinguished Research Professor of Vision Science at York University. He received his doctorate in Computer Science from the University of Toronto. After a postdoctoral fellowship in Cardiology at Toronto General Hospital, he joined the University of Toronto on faculty in Computer Science and in Medicine. In 1980 he founded the highly respected Computer Vision Group at the University of Toronto, which he led for 20 years. He was recruited to move to York University in 2000 as Director of the Centre for Vision Research. He has been a Canadian Heart Foundation Research Scholar (1981-83), a Fellow of the Canadian Institute for Advanced Research (1985-95) and Canada Research Chair in Computational Vision (2003-2017). He has received many awards and honours including several best paper awards, the 2006 Canadian Image Processing and Pattern Recognition Society Award for Research Excellence and Service, the 1st President’s Research Excellence Award by York University on the occasion of the University’s 50th anniversary in 2009, the 2011 Geoffrey J. Burton Memorial Lectureship from the United Kingdom's Applied Vision Association for significant contribution to vision science. He was elected as Fellow of the Royal Society of Canada in 2010 and was awarded its 2015 Sir John William Dawson Medal for sustained excellence in multidisciplinary research, the first computer scientist to be so honoured. Over 125 trainees have passed through his lab. His current research focuses on a comprehensive theory of visual attention in humans. A practical outlet for this theory forms a second focus, embodying elements of the theory into the vision systems of mobile robots.
Cosimo Distante received the degree in Computer Science in 1997 at the University of Bari and PhD in Engineering in 2001 at University of Salento. In 1998 he has been visiting researcher at the Computer Science Department of the University of Massachusetts at Amherst MA (USA) where has worked in the context of Perceptual Robotics and Artificial Neural Networks systems. He served as a teaching Assistant of the Artificial Intelligence Class of the University of Massachusetts. In 2001 he joined the Italian National Research Council CNR leading the signal and image processing laboratory. In 2009 he joined the National Institute of Optics. Since 2003 Dr. Distante is contract professor on “Image Processing” and “Pattern Recognition” in computer engineering at the University of Salento Italy. In 2011, Dr. Distante has been awarded with the national innovation Prize working capital PNI-Cube with the project Taggalo. In 2012 he has been awarded from the Senate President and Minister of Education University and Research of the Republic of Italy with the “Prize of the Prizes” for Innovation. Currently he is with the Institute of Applied Sciences and Intelligent systems ISASI “ScienceAPP” of the CNR. He chaired VAAM (Video analytics for Audience Measurement workshop), ACIVS 2016 (Int. Conf. on advanced concepts for intelligent vision systems) and IEEE AVSS 2017 (Int. Conf. on Advanced Video and Signal Based surveillance). His main research interests are in the field of computer vision and pattern recognition applied to: audience measurements, security and surveillance, robotics, medical imaging and manufacturing.
| Time/Date | Monday, Oct. 30 | Tuesday, Oct. 31 | Wednesday, Nov. 1 |
|---|---|---|---|
| 8:00 - 9:30 | Checkin and on-site registration |
Minicourse | Minicourse |
| 9:30 - 10:30 | Opening Cerimony | ||
| 10:00 - 10:30 | Coffee Break | ||
| 10:30 - 12:00 | Keynote Speaker 1 | Oral Session 3 | Keynote Speaker 2 |
| 12:00 - 14:00 | Lunch | ||
| 14:00 - 15:30 | Oral Session 1 | Oral Session 4 | Oral Session 6 |
| 15:30 - 16:00 | Coffee Break | ||
| 16:00 - 17:15 | Poster Session 1 | Poster Session 2 | Conference Meeting, Awards Ceremony and Closing Ceremony |
| 17:15 - 18:00 | Oral Session 2 | Oral Session 5 | |
| 19:00 - 22:00 | Conference Dinner | ||
Ricardo Farias, is bachelor's at Bacharelado em Fisica from Universidade Federal Fluminense (1984), master's at Computer Science from Universidade Federal do Rio de Janeiro (1996) and doctorate at Applied Mathematics And Statistics from State University Of New York At Stony Brook (2001). Has experience in Computer Science, acting on the following subjects: volume rendering, scientific visualization, visualization, volume visualization and high performance computing.
| Session/Time | Pattern recognition and applications |
| Oral Session 1 Monday 14:00-15:30 |
A computer vision system for soybean diseases recognition using UAVs: preliminary results |
| Human Epithelial type 2 (HEp-2) cell classification by using a Multiresolution Texture Descriptor | |
| Comparison between traditional texture methods and deep learning descriptors for detection of nitrogen deficiency in maize crops | |
| HEp-2 cell image classification based on Convolutional Neural Networks | |
| Combining Deep Learning and Multi-Class Discriminant Analysis for Granite Tiles Classification | |
| Session/Time | Feature extraction, descriptors and shape analysis |
| Oral Session 2 Monday 17:15-18:00 |
Automated Feature Extraction from Breast Masses using Multiscale Fractal Dimension |
| A novel method for shape analysis based on statistics of Euclidean distances | |
| Session/Time | Image segmentation and texture analysis |
| Oral Session 3 Tuesday 10:30-12:00 |
A comparison between two approaches to segment overlapped chromosomes in microscopy images |
| Multi-class Segmentation of Satellite Images by Color Mixture and Neural Network | |
| Exploring fuzzy numbers for image texture analysis | |
| Segmentation of the prostate gland in images using prior knowledge and level set method | |
| A novel method for fingerprint image segmentation based on Adaptative Gabor filters | |
| Fully Convolutional Neural Network for Occular Iris Semantic Segmentation | |
| Session/Time | Image/video analysis |
| Oral Session 4 Tuesday 14:00-15:30 |
Automatic Vehicle Count in Multiple Climatic and Illumination Conditions |
| Aerial image analysis for estimation of ground traversal difficulty in robot navigation | |
| A Replacement Based Video De-interlacing Technique by Feathering Effect Detection and Artifact Agglomeration Index | |
| Image Colorization with Neural Networks | |
| A Study of Swimmers Detection in Beach Images | |
| Session/Time | SLAM, Visual Odometry and Motion Estimation |
| Oral Session 5 Tuesday 17:15-18:00 |
Backward Motion for Estimation Enhancement in Sparse Visual Odometry |
| Tracking Spatially Distributed Features in KLT Algorithms for RGB-D Visual Odometry | |
| Accuracy Analysis of Augmented Reality Markers for Visual Mapping and Localization | |
| Session/Time | Biometrics |
| Oral Session 6 Wednesday 14:00-15:30 |
Optimizing a Homomorphic Filter for Illumination Compensation In Face Recognition Using Population-based Algorithms |
| CNNFusion-Gender: fusion facial parts methodology for gender classification in the wild | |
| Precise eye localization using the new multiscale high-boost Weber local filter | |
| Biometric Recognition based on Fingerprint: A Comparative Study | |
| Analysis of Wavelet Families for Face Recognition | |
| Biometric iris classification when the eyes pupil reacts to light |




