Schedule ISLA Colloquium 2006

Every talk runs from 11.30 till 12.30 and is held in room F0.13 Kruislaan 403.

If you click on the titles in the table below you will see the abstract of the talk.

More information is found on the schedule page of the ISLA SOOS.

Date Speaker Title
Jan 17 Jan-Mark Geusebroek Cancelled
Jan 24 Balder ten CateHow to design nice languages
Feb 7 Theo GeversColor in Computer Vision
Feb 28 Nikos VlassisBayesian Reinforcement Learning
Mar 21 Arnold SmeuldersSTART 10.30 Objects and objections
Apr 11 ICT Kenniscongres RAI ICT Kenniscongres RAI
May 2 Larry S. Davis (NVPHBV)Spring meeting of NVPHBV
May 23 Marcel WorringBrowsing Visual Collections
May 30 Maarten de RijkeConsumer Generated Text
Jun 13 Ben Kröse Digital Living: challenges for computational intelligence research
Jul 4 Cor VeenmanForensic Intelligence: Pattern Recognition in Forensic Practice
Sep 5No colloquium
Sep 26 Sennay Ghebreab Brain reading: decoding mental states of humans from functional neuroimaging data
Oct 17 Innovatiemarkt van STW Utrecht
Nov 7 Dariu Gavrila SMART CARS (THAT SEE/SAVE PEDESTRIANS)
Nov 21 Fall Meeting NVPHBV CWI Zaal Z.011
Dec 19 Giang P. Nguyen (ISIS) Promotie Aula UvA.

Speakers, their titles and their abstracts

Date
Jan 17
Speaker
Jan-Mark Geusebroek
Title
Cancelled.
Abstract
Date
Jan 24
Speaker
Balder ten Cate
Title
How to design nice languages
Abstract
Many issues play a role in the design of logical languages (such as query languages, knowledge representation formalisms, and specification languages). There is a well known trade-off between expressivity (how much you can say in a language) and complexity (how difficult it is to reason about expressions in the language), but there are also many other, less known, mathematically interesting interactions between desirable properties of such languages.

Taking the XML path language XPath as an example, I will discuss some of these properties and the way they interact with eachother. In doing so, I will cover some recent work of Maarten Marx and myself, as well as plans for my VENI project, which has just been accepted.

Date
Feb 7
Speaker
Theo Gevers
Title
Color in Computer Vision
Abstract
Color information has become a very useful information cue in computer vision. In this talk, an overview will be given on the use of color in the area of feature extraction, object recognition, and visual tracking. Physical models and learning techniques are discussed to obtain invariance and discriminative power. Further, the detection and classification of local structures (i.e. edges, corners, and T-Junctions) in color images is discussed. Finally, a few applications are presented in the context of image/video retrieval and player tracking in sport video.
Date
Feb 28
Speaker
Nikos Vlassis
Title
Bayesian Reinforcement Learning
Abstract
Reinforcement Learning (RL) refers to a class of methods addressing the problem of agent decision making under uncertainty. This problem can often be formalized as a Markov decision process (MDP), in which case optimal decision making corresponds to computing an optimal policy of this MDP. When the environment model (stochastic dynamics) is known, an MDP optimal policy can be easily computed by dynamic programming. When the environment model is unknown, the agent must learn its policy online by 'exploring' the environment. But what is the best way to explore an unknown environment? In this talk I'll describe Bayesian RL, an approach that in principle allows us solve the RL exploration problem optimally. The main idea is to form beliefs over the space of all possible environment models, and compute an optimal policy over that belief space. However, searching for policies over an infinitely dimensional belief space of models is a daunting task, making Bayesian RL a notoriously difficult problem to solve. In this talk I'll present some recent developments in the theory of Bayesian RL, which open new possibilities for the development of practical algorithms.
Date
Mar 21
Speaker
Arnold Smeulders
Title
Objects and objections
Abstract
In the talk I discuss the notion of an object in computer vision. The segmentation of a scene is described as the delineation of objects in the image field and generally believed to be the first processing step of human and computer vision alike defining the presence or absence of objects in an image. This is in contrast to the current wide believe in computer vision that universal algorithm for segmentation do not exist or are very hard anyway. In this ongoing debate I give a definition of segmentation and an overview of different brands of segmentation algorithms.
Date
May 23
Speaker
Marcel Worring
Title
Browsing Visual Collections
Abstract
The semantic gap between low level visual data and conceptual interpretation of the same data dictates that interactive browsing is an essential element of any visual information system. Such interactive browsing is a complex interplay between analysis of the data, visualization and user feedback. To structure the design of such methods we have developed the query space in our "CBIR at the end of the early years" paper. This query space is composed of the active dataset, features, a similarity function, interpretations and the relations among the four components. Since the early years several new insights in the characteristiscs of the query space have been gained. In this talk we will elaborate on the relation between different tasks, the role of large scale high-level indexing and new feedback and visualization methods.
Date
May 30
Speaker
Maarten de Rijke
Title
Consumer Generated Text
Abstract
Recent years have seen a rapid increase in the amount of consumer generated content that's available on the web. YouTube (for video sharing) has now entered the top 25 of most visited web sites. Before that Flickr rose to fame with its photo sharing facilities. And before that blogs had arrived on the scene. The massive availability of consumer generated content offers many challenges and opportunities for anyone interested in developing search, discovery, and analysis tools for web content. In this talk I will deal with consumer generated text, and, more specifically, with blogs. I will report on two research lines that are being pursued within the ILPS group. One deals with moodviews.com, a collection of tools for tracking streams of mood-annotated blog texts. The other deals with hierarchical language models for capturing a blogger's profile. One application of these models is in contextual advertisement on personal blogs: state-of-art ad placement methods for non-blog web content are not effective for personal blogs. An alternative method based on hierarchical language models proves to be much more effective.
Date
June 13
Speaker
Ben Kröse
Title
Digital Living: challenges for computational intelligence research
Abstract
There is an increase of ICT in residential environments: smart homes are becoming popular, in particular for monitoring purposes in elderly care. The systems which are being used consist of many sensors distributed in the home, and methods from the field of computational intelligence are used for data analysis. In the presentation I will focus on three aspects of these smart homes. First I will focus on algorithms for behaviour analysis of the humans and the relation with earlier work on multi camera surveillance. Then I will report on the Cogniron project, where we study (cognitive) representations for the interaction with humans. Thirdly I will present results of a study on the acceptance of ICT (the Philips 'iCat') by elderly.
Date
July 4
Speaker
Cor Veenman
Title
Forensic Intelligence: Pattern Recognition in Forensic Practice
Abstract
In the forensic practice, the number and size of available databases is growing rapidly. These databases range from biometrics of convicted people, to case report databases and case related environmental or drug samples. Forensic Intelligence deals with processing these databases in order to obtain useful hypotheses and to evaluate available evidence. In this talk I will give some research directions and examples of work in progress. First, multi-modal biometrics is an important direction for further research. Especially in forensic applications partial profiles are common and combined biometrics enable to narrow down the group of possible suspects. Another type of research is the prediction of drug types based on its composition in elements. This results in high dimensional classification problems that require specialized models.
Date
September 26
Speaker
Sennay Ghebreab
Title
Brain reading: decoding mental states of humans from functional neuroimaging data.
Abstract
In cognitive neuroscience, a trend can be observed toward psychophysical experiments involving naturalistic scene stimuli rather than simple controlled stimuli such as images of lines with predefined orientations. In computer science, a trend can be observed toward systems that enable automatic scene characterization and interpretation on the basis of objectively defined (statistical) scene features and classification schemes. In neuroimaging analysis, a trend can be seen toward pattern-based data analysis taking into account the full spatial pattern of brain activity rather than concentrating on specific brain regions. These trends are rapidly converging to a new research area: decoding mental states of humans from functional neuroimaging data. This research area aims at identifying, understanding and simulating processes and representations involved in the interpretation of natural stimuli such as real world scene by combining psychophysical and computational experiments with multivariate pattern analysis techniques. In this talk I will elaborate on our research in mapping brain activation data to natural sensory stimulation data and report on our participation in the brain reading competition.
Date
November 7
Speaker
Dariu M. Gavrila, DaimlerChrysler R&D, Ulm, Germany University of Amsterdam, Amsterdam, The Netherlands
Title
SMART CARS (THAT SEE/SAVE PEDESTRIANS)
Abstract
I'll start with a short overview of the rapid developments in the intelligent vehicle field over the past 2-3 years. The main part of the talk then covers recent progress at DaimlerChrysler on a viable vision-based pedestrian safety system [1]. I will focus on the pedestrian classification sub-problem, describing a recent study [2] which examined multiple feature-classifier combinations with respect to their ROC performance and efficiency. The underlying dataset, involving several thousands of pedestrian samples is downloadable as part of a new-to-be-established benchmark on pedestrian/object classification. I furthermore discuss semi- and fully automated techniques for enlarging the training set w.r.t. the target class. The performance of the DaimlerChrysler pedestrian system was extensively tested in real urban traffic. But I also present the outcome of some remarkable PreCrash experiments on the test track (with real pedestrians) ... 
[1] D. M. Gavrila and S. Munder. "Multi-cue Pedestrian
    Detection and Tracking from a Moving Vehicle". To
    appear in IJCV, Feb/March 2007.

[2] S. Munder and D. M. Gavrila. "An Experimental Study
    on Pedestrian Classification", PAMI, vol.28, nr.11, 2006.
Date
Tuesday 21 November 2006
Speakers
Arnold Smeulders, Max Viergever, Marcel Reinders and others
Title
Fall Meeting "25th Anniversary of the NVPHBV"
Abstract 
  *Fall Meeting "25th Anniversary of the NVPHBV" *
  
  Date: Tuesday 21 November 2006
  Local organizer: Informatics Institute of the University of Amsterdam
  Address:, CWI - lecture room Z.011 Kruislaan 413, Amsterdam
  
  We cordially invite you to attend the fall meeting of the NVPHBV in  
  celebration of its 25th anniversary. The program starts at 10.00 and 
  includes three invited keynote presentations, several oral presentations 
  by NVPHBV members centered around the 25th ledenvergadering. We start 
  the day with coffee (09.30), serve lunch and end with drinks. We will 
  also distribute the CDROM "Fifth Quinquinnial Review" to which many of 
  you have contributed.
  
  Invited keynote speakers
  Professor Arnold Smeulders (University of Amsterdam)
  Professor Max Viergever (University Medical Center Utrecht)
  Professor Marcel Reinders (Delft University of Technology)
  
  Call for papers
  Besides the keynote lectures we have several slots for presentations by 
  our members. Please submit a title (with abstract) to
  peter.kruizinga@oce.com (with a cc to nvphbv@qi.tnw.tudelft.nl) before 1 
  November 2006. The definitive program will be sent to you on 6 November 
  2006.
  
  Registration
  Please register as soon as possible, but no later than 17 November 2006, 
  by sending an email to Mrs. Virginie Mes
Date
Once
Speaker
Leo Dorst
Title
tba
Abstract
Date
tba
Speaker
Frans Groen
Title
Intelligent Autonomous Systems: Past, present and future?
Abstract
The well-known sense-think-act loop is characteristic for autonomous systems. Closing this loop enables analysis of the result of the action and so learning of goal directed behaviour. To create an autonomous system means that two essential components are needed besides intelligence: perception and actuation. Autonomous systems can be biological inspired, that forms a proof of existence, but on the other hand an artificial technical system gives also the freedom to incorporate non-human sensing.

In the past the focus has been on single agent systems, which learn certain tasks. The development towards real-world multi-agents systems was reflected in our group by the participation in RoboCup and in the DECIS lab. Multi-agent collaborative systems results in distributed sensing and requires distributed decision making. When no direct decision making is involved the first aspect is closely related to sensor networks. The complexity of the problem increases exponentially with the number of agents, so how to come up with approximate methods to solve this problem is an essential question.

You could debate whether autonomous systems are what you need in real-world applications. In the end the human is in control and systems are only in certain aspects autonomous (e.g. in sensor management and sensor data fusion). The trend is towards the cooperation of human and artificial agents. This cooperation can be present both in sensing and in the assistance to human decision making.