scholarly journals Grasping Partly Occluded Objects: Effects of Global Stimulus Information on Action

Perception ◽  
10.1068/p6158 ◽  
2009 ◽  
Vol 38 (2) ◽  
pp. 200-214 ◽  
Author(s):  
Janneke Lommertzen ◽  
Rob van Lier ◽  
Ruud G J Meulenbroek
1983 ◽  
Vol 49 (6) ◽  
pp. 1349-1363 ◽  
Author(s):  
J. E. Dayhoff ◽  
G. L. Gerstein

In this paper we apply the two methods described in the companion paper (4) to experimentally recorded spike trains from two preparations, the crayfish claw and the cat striate cortex. Neurons in the crayfish claw control system produced favored patterns in 23 of 30 spike trains under a variety of experimental conditions. Favored patterns generally consisted of 3-7 spikes and were found to be in excess by both quantized and template methods. Spike trains from area 17 of the lightly anesthetized cat showed favored patterns in 16 of 27 cases (in quantized form). Some patterns were also found to be favored in template form; these were not as abundant in the cat data as in the crayfish data. Most firing of the cat neurons occurred at times near stimulation, and the observed patterns may represent stimulus information. Favored patterns generally contained up to 7 spikes. No obvious correlations between identified neurons or experimental conditions and the generation of favored patterns were apparent from these data in either preparation. This work adds to the existing evidence that pattern codes are available for use by the nervous system. The potential biological significance of pattern codes is discussed.


Perception ◽  
1995 ◽  
Vol 24 (11) ◽  
pp. 1333-1364 ◽  
Author(s):  
Lothar Spillmann ◽  
Birgitta Dresp

The study of illusory brightness and contour phenomena has become an important tool in modern brain research. Gestalt, cognitive, neural, and computational approaches are reviewed and their explanatory powers are discussed in the light of empirical data. Two well-known phenomena of illusory form are dealt with, the Ehrenstein illusion and the Kanizsa triangle. It is argued that the gap between the different levels of explanation, bottom—up versus top—down, creates scientific barriers which have all too often engendered unnecessary debate about who is right and who is wrong. In this review of the literature we favour an integrative approach to the question of how illusory form is derived from stimulus configurations which provide the visual system with seemingly incomplete information. The processes that can explain the emergence of these phenomena range from local feature detection to global strategies of perceptual organisation. These processes may be similar to those that help us restore partially occluded objects in everyday vision. To understand better the Ehrenstein and Kanizsa illusions, it is proposed that different levels of analysis and explanation are not mutually exclusive, but complementary. Theories of illusory contour and form perception must, therefore, take into account the underlying neurophysiological mechanisms and their possible interactions with cognitive and attentional processes.


2006 ◽  
Vol 18 (6) ◽  
pp. 1441-1471 ◽  
Author(s):  
Christian Eckes ◽  
Jochen Triesch ◽  
Christoph von der Malsburg

We present a system for the automatic interpretation of cluttered scenes containing multiple partly occluded objects in front of unknown, complex backgrounds. The system is based on an extended elastic graph matching algorithm that allows the explicit modeling of partial occlusions. Our approach extends an earlier system in two ways. First, we use elastic graph matching in stereo image pairs to increase matching robustness and disambiguate occlusion relations. Second, we use richer feature descriptions in the object models by integrating shape and texture with color features. We demonstrate that the combination of both extensions substantially increases recognition performance. The system learns about new objects in a simple one-shot learning approach. Despite the lack of statistical information in the object models and the lack of an explicit background model, our system performs surprisingly well for this very difficult task. Our results underscore the advantages of view-based feature constellation representations for difficult object recognition problems.


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