Archive for the 'computer vision' Category

show me your prefrontal cortex

Tuesday, March 6th, 2007


Together with collegues from London and Tokyo neuroscientist John-Dylan Haynes did an experiment (however up to now only with 21 test persons as it seems), where a person had to choose wether he/she wanted either to add or to substract two numbers. And even before the test persons saw the numbers and before they started to compute it was possible – by using a MRI brain scan – to tell with a 70% chance, what kind of desicion the person was going to make, or in other words: using the MRI the scientists could “read the mind” of the test persons (with a 70% chance). Freely chosen decisions are usually happening in the prefrontal cortex.


finding the right proportions

Monday, January 29th, 2007

Duchenne.jpgMécanisme de la Physionomie Humaine by Guillaume Duchenne from wikipedia

The face of a human (lets include the ears) is the part of a human body which is usually adressed first as an interface to the human mind and body behind it. And most often it stays the main interface to be used by other humans (and animals). After a first contact people may shake hands a.s.o. but still the face is usually the starting point for facing each other and together with subtle gestures it can give way to a very fast judgements about the personality of people.

So it is no wonder that a portrait of a person almost always includes the face. Faces usually move and the movement is very important in the perception of a face. However in a portrait painting or a portrait fotograph there is no movement and – still – portraits describe the person behind the face – at least to a certain extend. It is also a wellknown rumour (I couldnt find a study on it) that a drawing reflects the painter to a certain extend, like e.g. fat artists apparently tend to draw persons more solid then thin artists a.s.o.

So it is no wonder that people try to find laws, for e.g. when a (still) face looks attracting to others and when not. Facial expressions (see above image) play a significant role (see also this old randform post). But also cultural things etc. are important. But still – if we assume to have eliminated all these factors as best as possible (by e.g. comparing bold black and white faces of the same age group looking emotionless) – then is there still a link between the appearance of a face and the interpretation of the human character behind the face? How stable is this interpretation, like e.g. when the face was distorted by violence or an accident? How much does the physical distortion parallel the psychological?

All these studies are of course especially interesting when it comes to constructing artificial faces, like in virtual spaces or for humanoid robots (e.g. here) (see also this old randform post).

Similar questions were also studied in a nice future face exhibition at the science museum in London organized by the Wellcome Trust.

An analytical method is to start with proportions, where there are some prominent old works, like Leonardo’s or Duerer’s studies, leading last not least to e.g. studies in artificial intelligence which for example link “beautiful” proportions to the low complexity of the corresponding encoded information.

These questions are a bit related to the question of how interfaces are related to processes of computing, also if one doesnt just think of robots. It concerns also questions of Human Computer Interactions as we saw above and finally Human Computer Human Interactions, which were thematized e.g. in our work seidesein.

update June 14th, 2017: according to nytimes (original article) researchers from caltech have apparently found the way how macaque monkeys encode images of faces in their brain. The article describes that the patterns of how 200 brain cells were firing could be translated into deviations form a “standard face” along certain axes, which span 50 dimensions, from the nytimes:

“The tuning of each face cell is to a combination of facial dimensions, a holistic system that explains why when someone shaves off his mustache, his friends may not notice for a while. Some 50 such dimensions are required to identify a face, the Caltech team reports.

These dimensions create a mental “face space” in which an infinite number of faces can be recognized. There is probably an average face, or something like it, at the origin, and the brain measures the deviation from this base.

A newly encountered face might lie five units away from the average face in one dimension, seven units in another, and so forth. Each face cell reads the combined vector of about six of these dimensions. The signals from 200 face cells altogether serve to uniquely identify a face.”

If I haven’t overseen something the article though doesn’t say, how or whether that “standard face” is connected to “simple face dimensions”, i.e. “easy to compute facial features” as mentioned above. By very briefly browsing/ diagonally reading in the original article I understand that the researchers pinpointed 400 facial features, 200 for shape and 200 for appearances and then looked in which directions those move for a set of faces, then extracted those “move directions” via a PCA and then noticed that specific cells first reacted mostly only to 6 dimensions and secondly that the firing rate varied, which apparently allowed to encode specific faces in a linear fashion in this 50 dimensional space. I couldn’t find out in this few minutes reading whether the authors give any indication on how e.g. the “shape points” (figure 1a in the image panel) move when moving along one of the 25 shape dimensions, i.e. in particular wether some kind of Kolmogorov complexity features could be extracted (as it seems to be done here) or not.

It is also unclear to me what these new findings mean for the “toilet paper wasting generation” in China.

By the way in this context I would like to link to our art work CloneGiz.

pattern ammunition

Monday, January 8th, 2007


In the sixties some semioticians studied among others the semiotics of photographies where they discovered e.g. the socalled “photographical paradox” (Barthes).


hopefully f.wishent tree

Friday, December 29th, 2006


The Java applet f.wish by boredom research (see also the interview on furtherfield)- is a graphical reinterpretation of the Lam Tsuen Wishing Trees on folly.

At f.wish you can hang your personal and public wishes (e.g. for next year) onto a tree and read those of others (see above).

f.wish has a nice spongy letter-from-spring-gravity simulation (with the partial use of the traer.physics library for processing). Sean Carroll of the physics blog cosmic variance was just discussing physics and in particular gravity in games like this (partially physically uncorrect) game but also a Ninja game and the book “physics of the buffyverse” (seems to be similar in intention to this book) were topics in his post.

Another gravity game has a possibility to change directions while flying but no walls and thus you may get lost in space easily. And there is a dial which shows you how far you are lost.


Friday, November 3rd, 2006

I finally managed to translate my article for the conference proceedings of the NMI2006 conference from german into english. There are a few additions, which are not included in the german version.

The article is a description of our installation seidesein. It gives an account on our motivations for creating seidesein but it explains a bit also our motivation for other daytar works.

The article is for download >>here or directly via the seidesein page.

I am very grateful for any feedback on this article.


Friday, October 27th, 2006


A new service from the viennese company systemone:

Retrievr lets you find flickr images by drawing rough sketches of them. Finding images on Flickr is mostly textual (tags, keywords) or social (contacts, friends, groups). Retrievr is, like images, visual. At the same time it’s our testbed for image retrieval algorithms, so that when you add an image to a page in System One, it gets you the potentially most similar pictures back in realtime.

It was not fair to test the retrieval with my above flower image (big one to the left) , as it bears a lot of fine structure….and consequently I got the above results back (images to the right)…:)

see also this related old randform post

via gizmodo

character recognition linked to physics engines

Friday, October 20th, 2006


A hidden Markov model as it usually appears in pattern recognition

Optical character recognition, usually abbreviated to OCR, is computer software designed to translate images of handwritten or typewritten text (usually captured by a scanner or a digitizer) into machine processable text. OCR is e.g. commercially used in PDA’s However “handwritten” characters do not need to be constrained to letters or simple symbols but could also be more complex shapes, if necessary also in 3D. The recognition of such shapes can also be interpreted as gesture recognition.


watery simulations

Wednesday, October 4th, 2006


Chemical reactions according to Stanfords CG lab

water again: water simulations are cool. However the big question is: WHAT IS A SIMULATION? I.e. at what point do we accept a thing to look physically realistic? Do we want it to look realistic?



Monday, September 18th, 2006


A classic in midi-to-graphics “generative” animation is “pipedream” by Dave Crognale and Wayne Lytle. It is sold together with other works by them on a DVD compilation via their website animusic. The “pipedream”-video itself is however also downloadable via the SIGGRAPH animation site on However if you have an ATI graphics card you can render it also in realtime via the ATI rendering-gadgets sites for MAC and Windows.

Wayne Lytle has worked also in scientific visualization, e.g. on this mathematical visualization video for string theorist Brian Greene.

uncanny paintings

Thursday, August 3rd, 2006


“empathic paintings” by Shugrina, Betke and Collomosse