Recognition of partially occluded objects using correlation filters with training

2005 ◽  
Author(s):  
J. A. Gonzalez-Fraga ◽  
Vitaly Kober ◽  
Josue Alvarez-Borrego
Keyword(s):  
Correlation Filters ◽  
Occluded Objects ◽  
Partially Occluded

scholarly journals Reliable Recognition of Partially Occluded Objects with Correlation Filters

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Alexey Ruchay ◽  
Vitaly Kober ◽  
Jose A. Gonzalez-Fraga
Keyword(s):  
Explicit Knowledge ◽  
Target Object ◽  
Correlation Filters ◽  
Occluded Objects ◽  
Training Stage ◽  
Objective Metrics ◽  
Key Points ◽  
Cluttered Background ◽  
Partially Occluded ◽  
Different Parts

Design of conventional correlation filters requires explicit knowledge of the appearance and shape of a target object, so the performance of correlation filters is significantly affected by changes in the appearance of the object in the input scene. In particular, the performance of correlation filters worsens when objects to be recognized are partially occluded by other objects, and the input scene contains a cluttered background and noise. In this paper, we propose a new algorithm for the design of a system consisting of a set of adaptive correlation filters for recognition of partially occluded objects in noisy scenes. Since the input scene may contain different fragments of the target, false objects, and background to be rejected, the system is designed in such a manner to guarantee equally high correlation peaks corresponding to parts of the target in the scenes. The key points of the system are as follows: (i) it consists of a bank of composite optimum filters, which yield the best performance for different parts of the target; (ii) it includes a fragmentation of the target into a given number of parts in the training stage to provide equal intensity responses of the system for each part of the target. With the help of computer simulation, the performance of the proposed algorithm for recognition partially occluded objects is compared with that of common algorithms in terms of objective metrics.

scholarly journals Phenomena of Illusory Form: Can We Bridge the Gap between Levels of Explanation?

Perception ◽  
1995 ◽  
Vol 24 (11) ◽  
pp. 1333-1364 ◽  
Author(s):  
Lothar Spillmann ◽  
Birgitta Dresp
Keyword(s):  
Feature Detection ◽  
Brain Research ◽  
Form Perception ◽  
Integrative Approach ◽  
Levels Of Explanation ◽  
Attentional Processes ◽  
Occluded Objects ◽  
Neurophysiological Mechanisms ◽  
Partially Occluded ◽  
Different Levels

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.

Photoelastic Analysis of Partially Occluded Objects With an Integral-Imaging Polariscope

2014 ◽  
Vol 10 (4) ◽  
pp. 255-262 ◽  
Author(s):  
Hector Navarro Fructuoso ◽  
Manuel Martinez-Corral ◽  
Genaro Saavedra Tortosa ◽  
Amparo Pons Marti ◽  
Bahram Javidi
Keyword(s):  
Integral Imaging ◽  
Occluded Objects ◽  
Photoelastic Analysis ◽  
Partially Occluded

Pigeons' Recognition of Partially Occluded Objects Depends on Specific Training Experience

Perception ◽  
10.1068/p5583 ◽  
2007 ◽  
Vol 36 (1) ◽  
pp. 33-48 ◽  
Author(s):  
Olga F Lazareva ◽  
Edward A Wasserman ◽  
Irving Biederman
Keyword(s):  
Specific Training ◽  
Training Experience ◽  
Occluded Objects ◽  
Partially Occluded

Recognition of Partially Occluded Objects Based on the Three Different Color Spaces (RGB, YCbCr, HSV)

3D Research ◽  
2015 ◽  
Vol 6 (3) ◽  
Author(s):  
Shiva Soleimanizadeh ◽  
Dzulkifli Mohamad ◽  
Tanzila Saba ◽  
Amjad Rehman
Keyword(s):  
Color Spaces ◽  
Occluded Objects ◽  
Different Color ◽  
Partially Occluded
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