0000000000114773
AUTHOR
Bertrand Zavidovique
Panel Summary One Model for Vision Systems?
This panel reports some considerations about the definition of vision-models. The panellists are scientists working on vision problems from different perspectives. The concept of model in vision seems to remain still open. In fact, it is dynamic, and context dependent. There exists the need for a better exchange of information, among biologists, engineers, physicists, and psychologists in order to improve our knowledge.
Pyramid symmetry transforms: From local to global symmetry
Pyramid computation is a natural paradigm of computation in planning strategies and multi-resolution image analysis. This paper introduces a new paradigm that is based on the concept of soft-hierarchical operators implemented in pyramid architecture to retrieve global versus local symmetries. The concept of symmetry is mathematically well defined in geometry whenever patterns are crisp images (two levels). Necessity for a soft approach occurs with multi-levels images and whenever the separation between object and background is subjective or not well defined. The paper describes two new pyramid operators to detect symmetries based on previously introduced conventional operators. For sake of …
Symmetry as an Intrinsically Dynamic Feature
Symmetry is one of the most prominent spatial relations perceived by humans, and has a relevant role in attentive mechanisms regarding both visual and auditory systems. The aim of this paper is to establish symmetry, among the likes of motion, depth or range, as a dynamic feature in artificial vision. This is achieved in the first instance by assessing symmetry estimation by means of algorithms, putting emphasis on erosion and multi- resolution approaches, and confronting two ensuing problems: the isolation of objects from the context, and the pertinence (or lack thereof) of some salient points, such as the centre of mass. Next a geometric model is illustrated and detailed, and the problem …
Panel Summary: Behavioural Models
The aim of this paper is to report the panel discussion on behavioural models of human or machine agents interacting with the environment. In particular the following hot points will been analysed: a framework for describing behaviour; learning and evolution; closure and teleonomy when it comes to behaviour; the perception-learning-planning loop; the information integration at the (pre)attentive level; knowing by acting and knowing by computing.
Face Expression Recognition through Broken Symmetries
Security systems, criminology, physical access control and man-machine interactions are examples of applications where recognition of human faces may be crucial. In the present paper a new signature, based on a measure of axial symmetry called DST, is proposed as a significant feature to analyze facial expressions. The measure of symmetry is an elaborate difference between the internal and external symmetry kernels of an object. The idea here is to use the evolution of the symmetry measure of a face over an ordered set of its sub-images. We claim that different evolutionary trends will represent different face expressions. The proposed signature has been tested on several face databases (ps…
S_Kernel: A New Symmetry Measure
Symmetry is an important feature in vision. Several detectors or transforms have been proposed. In this paper we concentrate on a measure of symmetry. Given a transform S, the kernel SK of a pattern is defined as the maximal included symmetric sub-set of this pattern. It is easily proven that, in any direction, the optimal axis corresponds to the maximal correlation of a pattern with its flipped version. For the measure we compute a modified difference between respective surfaces of a pattern and its kernel. That founds an efficient algorithm to attention focusing on symmetric patterns.
The S-kernel: A measure of symmetry of objects
In this paper we introduce a new symmetry feature named ''symmetry kernel'' (SK) to support a measure of symmetry. Given any symmetry transform S, SK of a pattern P is the maximal included symmetric sub-set of P for all directions and shifts. We provide a first algorithm to exhibit this kernel where the centre of symmetry is assumed to be the centre of mass. Then we prove that, in any direction, the optimal axis corresponds to the maximal correlation of a pattern with its symmetric version. That leads to a second algorithm. The associated symmetry measure is a modified difference between the respective surfaces of a pattern and its kernel. A series of experiments supports the actual algorit…
Kernel Based Symmetry Measure
In this paper we concentrate on a measure of symmetry. Given a transform S, the kernel SK of a pattern is defined as the maximal included symmetric sub-set of this pattern. A first algorithm is outlined to exhibit this kernel. The maximum being taken over all directions, the problem arises to know which center to use. Then the optimal direction triggers the shift problem too. As for the measure we propose to compute a modified difference between respective surfaces of a pattern and its kernel. A series of experiments supports actual algorithm validation.
A note on the iterative object symmetry transform
This paper introduces a new operator named the iterated object transform that is computed by combining the object symmetry transform with the morphological operator erosion. This new operator has been applied on both binary and gray levels images showing the ability to grasp the internal structure of a digital object. We present also some experiments on artificial and real images and potential applications.
The iterative object symmetry transform
This paper introduces a new operator named the Iterated Object Transform that is computed by combining the Object Symmetry Transform with the morphological operator erosion. This new operator has been applied on both binary and gray levels images showing the ability to grasp the internal structure of a digital object. We present some experiments on real images in face analysis.
Iterative Symmetry Detection: Shrinking vs. Decimating Patterns
This paper introduces a new mechanism that consists of applying a symmetry operator on an iteratively transformed version of the input image. The nature of the transformation characterizes the operator. Here, we consider the Object Symmetry Transform combined with the morphological operator erosion and the pyramid decimation respectively. The derived operators have been applied on both binary and gray levels images, comparing their ability to grasp the internal structure of a digital object. We present some experiments to evaluate their performances and check them for result quality versus computing complexity.
Soft Pyramid Symmetry Transforms
Pyramid computation is a natural paradigm of computation in planning strategies and multi-resolution image analysis. This paper introduces a new paradigm that is based on the concept of soft-hierarchical operators implemented in a pyramid architecture to retrieve global versus local symmetries. The concept of symmetry is mathematically well defined in geometry whenever patterns are crisp images (two levels). Necessity for a soft approach occurs whenever images are multi-levels and the separation between object and background is subjective or not well defined. The paper describes a new pyramid operator to detect symmetries and shows some experiments supporting the approach. This work has bee…
Panel Summary: Planning And Plasticity in Artificial and Natural Systems
Boncinelli underlined often, during our workshop, that simplest organisms are the more robust and they survived longer than more evolved organisms (what about the quality of their life?). This depends on the fact that complex systems either natural or artificial need for more complex controls. Moreover, planning strategies, one of the steps for finding optimal solutions, must be carefully designed and it is complex too.