Download - VUB Artificial Intelligence Lab
VUB Artificial Intelligence Lab
• Director: Prof. Dr. Luc Steels
• Expertise in– Complex Dynamical systems research– Artificial Life– Behavior-based robotics– Evolution of natural language– Cognitive modelling
Evolution of language
Language might be the key to intelligent behaviour. Research questions:
– What is needed in order to learn and produce linguistic utterances.
– How do humans conceptualise the world.– How does language evolve.
Language (and its components) is a complex dynamical system emerging from the interactions between individual language users.
Cognitive modelling
In order to investigate these issues, we use agent-based cognitive modelling
For example– Evolution of phonemes: vocal tract and auditory perception is
faithfully modelled, together with a phonetic memory which behaves as observed human behavior.
Talking Heads
• Large scale experiment started in 1999 to study the emergence and evolution of lexicons.
Agent based Combined perception and
language Lacked action and syntax.
Extending the Talking Heads
Talking Heads lacked two important components– Compositionality– Action
New experiment to solve– Stereo colour vision.– Learning in action space.– Associating perception, action,
conceptualisation and language.
VUB Electronics & Information Processing Lab
• Director: Prof. Dr. Jan Cornelis
• Expertise in– Compression of Images and Video – Multimedia Applications– Remote Sensing – Satellite Image Processing– Pattern Recognition – Classifier Models and
Evaluation/Applications– Medical Image Processing - Registration, Segmentation,
Analysis, Tele-Medicine– Applied Numerical Analysis and Inverse Problems – Theory and
Applications– Computer Vision – Computational Vision, Robotics and
Applications– Landmine Detection – Remote Sensing, Subsurface Imaging
Multimedia Applications• Image Compression
– JPEG, JPEG2000– Segmentation-based Coding– Volumetric Wavelet Coding (Medical, Remote Sensing)
• Video Compression– MPEG-x, H.26x– In-band Wavelet Video Coding
• Video Segmentation and Key Frame Extraction– MPEG-7
• Interactive Television• Synthetic/Natural Hybrid Coding
– MPEG-4: Facial Animation, Advanced Animation Framework (AFX), Mesh-Coding
• Memory Efficient HW/SW Implementations of Multimedia Systems
Frank
Sabine
Applied Numerical Analysis& Inverse Problems
• Applied Numerical Analysis – Subspace Algorithms– Nonlinear Optimization– Radial Basis Functions (RBF) Techniques
• Inverse Problems– Focus on Numerical Aspects (instead of more classical
functional analysis approach)– Multi-level Regularization
• Application Domains– Electrical Impedance Tomography (EIT)
… (General Medical, Dental Diagnosis, Subsurface Imaging)
– Tomographic Ground Penetrating Radar (GPR) Imaging… (Landmine Detection)
– Intra-Oral Digital Subtraction Radiography… (Hidden Caries Phenomenon)
Computer Vision• Computational Vision
– Inverse Problems for Scene Reconstruction
– Differential Equation Models in Vision
– Scale Space Theory for Image Analysis
– Model based image analysis/understanding
• Perception for Robotics– Active Visual Perception
– Visual Feedback for Control and Navigation
Computer Vision• Applications
– Measurement and interpretation of visual motion
– Motion and 3D shape from image sequences – Segmentation of Image/Motion – Perceptual Grouping– Face detection, tracking and animation– Visual tracking (surveillance)– Visual guidance/navigation of mobile robots
Vision Problems
Reconstruction– estimate parameters of external 3D world.
Segmentation– partition I(x,y,t) into subsets of separate objects.
Visual Control– visually guided locomotion and manipulation
Recognition– classes: face vs. non-face,– activities: gesture, expression.
Reconstruction
Computer vision address the inverse problem: given an image/multiple images, reconstruct the scene geometry, motion parameters, …
Single images adequate given knowledge of object class
Multiple images make the problem easier, but not trivial as corresponding points must be identified.
knowledge of object class
Original image
Detected line segments
Selected rooftops
All possible rooftop hypotheses
Line segment detection
MRF labeling
Building detectionMRF labeling
Perceptual grouping
Structure from Motion
Problem Statement: 3D line orientation (r) estimation from motion
Objective functional
PDE Model: vector-valued, reaction-diffusion
Propertiesdiffusion system coupled through the reaction term from 2D motion constraint, three processes evolve simultaneously; L-curve technique for estimating regularization parameter.
Experimental Results
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Governing PDEs
Multigrid Framework
Experimental Results
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Challenges in Reconstruction
Finding correspondences automatically
Optimal estimation of structure from n views under perspective projection
Models of reflectance and texture for natural materials and objects
Image Segmentation
Boundaries of image regions defined by a number of attributes Brightness/color
TextureMotiondepth
ApproachMultiscale region-based segmentation
Multiscale region-based segmentation
Motivation Partitioning of multivalued images into meaningful objects.
Main issues • Generation of a multiscale tower
using non-linear diffusion filtering..• Segmentation using gradient-driven
watersheds: Methods
• Hierarchical Segmentation Using Dynamics of Contours of Multiscale Color Gradient Watersheds: fine-to-coarse region merging using a saliency measure
• Hierarchical Labeling of Contours: Introduction of a causal Bayesian model to the scale space hierarchy of watersheds. Coarse-to-fine labeling using a MAP criterion based on a contour saliency measure and transition probabilities.
Segmentation examples
Temporal Segmentation: Tracking
Challenges in Segmentation
Interaction of multiple cues
Local measurements to global percepts
Interplay of image-driven and object model driven processing
Control
Visual feedback signal for control for tasks such as grasping and moving
Visual feedback for guiding locomotion Obstacle avoidance for a moving robot Lateral and longitudinal control of driving
Challenges in control
Delay in feedback loop due to visual processing
Hierarchies in sensory motor control
Open loop or closed loop Discrete planning or continuous control