On differential invariants of planar curves and recognizing partially occluded planar shapes

1995 ◽  
Vol 13 (3-4) ◽  
pp. 227-250 ◽  
Author(s):  
Alfred M. Bruckstein ◽  
Arun N. Netravali
Keyword(s):  
Differential Invariants ◽  
Planar Curves ◽  
Planar Shapes ◽  
Partially Occluded

Similarity-invariant signatures for partially occluded planar shapes

1992 ◽  
Vol 7 (3) ◽  
pp. 271-285 ◽  
Author(s):  
Alfred M. Bruckstein ◽  
Nir Katzir ◽  
Michael Lindenbaum ◽  
Moshe Porat
Keyword(s):  
Invariant Signatures ◽  
Planar Shapes ◽  
Similarity Invariant ◽  
Partially Occluded

SIMILARITY AND AFFINE NORMALIZATION OF PARTIALLY OCCLUDED PLANAR CURVES USING FIRST AND SECOND DERIVATIVES

1998 ◽  
Vol 31 (10) ◽  
pp. 1551-1556 ◽  
Author(s):  
STEPHEN L. ADLER ◽  
RANGANATHAN KRISHNAN
Keyword(s):  
Planar Curves ◽  
Second Derivatives ◽  
Partially Occluded

RECOGNITION OF PARTIAL PLANAR SHAPES IN LIMITED MEMORY ENVIRONMENTS

1990 ◽  
Vol 04 (04) ◽  
pp. 603-628 ◽  
Author(s):  
SANTANU CHAUDHURY ◽  
S. SUBRAMANIAN ◽  
GUTURU PARTHASARATHY
Keyword(s):  
Heuristic Search ◽  
Recognition Algorithm ◽  
Two Stage ◽  
Second Stage ◽  
Limited Memory ◽  
Occluded Objects ◽  
Planar Shapes ◽  
Problem Instances ◽  
Stage Matching ◽  
Partially Occluded

Industrial vision systems should be capable of recognising noisy objects, partially occluded objects and randomly located and/or oriented objects. This paper considers the problem of recognition of partially occluded planar shapes using contour segment-based features. None of the techniques suggested in the literature for solving the above problem guarantee reliable results for problem instances which require memory in excess of what is available. In this paper, a heuristic search-based recognition algorithm is presented, which guarantees reliable recognition results even when memory is limited. This algorithm identifies an object, the maximum portion of whose contour is visible in a conglomerate of objects. For increasing efficiency of the method, a two-stage recognition scheme has been designed. In the first phase, a relevant subset of the known model shapes is chosen and in the second stage, matching between the unknown shape and elements of the relevant subset is attempted using the above approach. The technique is general in the sense that it can be used with any kind of contour features. To evaluate the efficiency of the method, experimentation was carried out using polygonal approximations of the object contours. Results are cited for establishing the effectiveness of the approach.

Matching of partially occluded planar curves

1995 ◽  
Vol 28 (2) ◽  
pp. 199-209 ◽  
Author(s):  
Arie Pikaz ◽  
Its'hak Dinstein
Keyword(s):  
Planar Curves ◽  
Partially Occluded

Recognition of partially occluded 3D objects

1989 ◽  
Vol 136 (2) ◽  
pp. 124
Author(s):  
Ming-Hong Chan ◽  
Hung-Tat Tsui
Keyword(s):  
3D Objects ◽  
Partially Occluded

scholarly journals Affine Subspaces of Curvature Functions from Closed Planar Curves

2021 ◽  
Vol 76 (2) ◽  
Author(s):  
Leonardo Alese
Keyword(s):  
Arc Length ◽  
Planar Curves ◽  
Affine Subspaces ◽  
Planar Curve ◽  
Real Functions ◽  
Discrete Counterpart ◽  
Equivalent Conditions

AbstractGiven a pair of real functions (k, f), we study the conditions they must satisfy for $$k+\lambda f$$ k + λ f to be the curvature in the arc-length of a closed planar curve for all real $$\lambda $$ λ . Several equivalent conditions are pointed out, certain periodic behaviours are shown as essential and a family of such pairs is explicitely constructed. The discrete counterpart of the problem is also studied.

scholarly journals The COVID-19 pandemic masks the way people perceive faces

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Erez Freud ◽  
Andreja Stajduhar ◽  
R. Shayna Rosenbaum ◽  
Galia Avidan ◽  
Tzvi Ganel
Keyword(s):  
Social Interactions ◽  
Face Perception ◽  
Face Processing ◽  
Qualitative Change ◽  
Daily Activities ◽  
Human Face ◽  
Human Face Recognition ◽  
Processing Abilities ◽  
Partially Occluded ◽  
The Way

AbstractThe unprecedented efforts to minimize the effects of the COVID-19 pandemic introduce a new arena for human face recognition in which faces are partially occluded with masks. Here, we tested the extent to which face masks change the way faces are perceived. To this end, we evaluated face processing abilities for masked and unmasked faces in a large online sample of adult observers (n = 496) using an adapted version of the Cambridge Face Memory Test, a validated measure of face perception abilities in humans. As expected, a substantial decrease in performance was found for masked faces. Importantly, the inclusion of masks also led to a qualitative change in the way masked faces are perceived. In particular, holistic processing, the hallmark of face perception, was disrupted for faces with masks, as suggested by a reduced inversion effect. Similar changes were found whether masks were included during the study or the test phases of the experiment. Together, we provide novel evidence for quantitative and qualitative alterations in the processing of masked faces that could have significant effects on daily activities and social interactions.

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