scholarly journals Image deformation as a cue to material category judgment

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Takahiro Kawabe ◽  
Rok Kogovšek
Keyword(s):  
Category Judgment ◽  
Image Deformation

Racial category judgment from appearance is categorical, and asymmetrical for men but not women

2004 ◽  
Author(s):  
Elizabeth N. Bartmess ◽  
Lawrence A. Hirschfeld
Keyword(s):  
Category Judgment ◽  
Racial Category

Memorial processes and category judgment

1969 ◽  
Author(s):  
L. M. Ward ◽  
G. R. Lockhead
Keyword(s):  
Category Judgment

Modifying Perceived Size of a Handled Object through Hand Image Deformation

2013 ◽  
Vol 22 (3) ◽  
pp. 255-270 ◽  
Author(s):  
Yuki Ban ◽  
Takuji Narumi ◽  
Tomohiro Tanikawa ◽  
Michitaka Hirose
Keyword(s):  
Visual Representation ◽  
Shape Perception ◽  
Size Perception ◽  
Visual Object ◽  
Display System ◽  
Haptic Interaction ◽  
Image Deformation ◽  
Virtual Objects ◽  
The Difference ◽  
Hand Image

In this study, we aim to construct a perception-based shape display system to provide users with the sensation of touching virtual objects of varying shapes using only a simple mechanism. Thus far, we have proved that identified curved surface shapes or edge angles can be modified by displacing the visual representation of the user's hand. However, using this method, we cannot emulate multifinger touch, because of spatial unconformity. To solve this problem, we focus on modifying the identification of shapes using two fingers by deforming the visual representation of the user's hand. We devised a video see-through system that enables us to change the perceived shape of an object that a user is touching visually. The visual representation of the user's hand is deformed as if the user were handling a visual object; however, the user is actually handling an object of a different shape. Using this system, we conducted two experiments to investigate the effects of visuo-haptic interaction and evaluate its effectiveness. One is an investigation on the modification of size perception to confirm that the fingers did not stroke the shape but only touched it statically. The other is an investigation on the modification of shape perception for confirming that the fingers dynamically stroked the surface of the shape. The results of these experiments show that the perceived sizes of objects handled using a thumb and other finger(s) could be modified if the difference between the size of physical and visual stimuli was in the −40% to 35% range. In addition, we found that the algorithm can create an effect of shape perception modification when users stroke the shape with multiple fingers.

scholarly journals LARGE SCALE CITY MAPPING USING SATELLITE IMAGERY / KOSMINIŲ NUOTRAUKŲ IŠ GOOGLE EARTH, TAIKOMŲ MIESTAMS KARTOGRAFUOTI STAMBIUOJU MASTELIU, REKTIFIKAVIMAS / РЕКТИФИКАЦИЯ КОСМИЧЕСКИХ СНИМКОВ ИЗ GOOGLE EARTH ДЛЯ КРУПНОМАСШТАБНОГО КАРТОГРАФИРОВАНИЯ ГОРОДОВ

2012 ◽  
Vol 37 (4) ◽  
pp. 168-171 ◽  
Author(s):  
Birutė Ruzgienė ◽  
Qian Yi Xiang ◽  
Silvija Gečytė
Keyword(s):  
Satellite Imagery ◽  
Large Scale ◽  
Modern Technology ◽  
Google Earth ◽  
Aerial Images ◽  
Control Points ◽  
Image Rectification ◽  
Image Deformation ◽  
Map Construction ◽  
Short Period

The rectification of high resolution digital aerial images or satellite imagery employed for large scale city mapping is modern technology that needs well distributed and accurately defined control points. Digital satellite imagery, obtained using widely known software Google Earth, can be applied for accurate city map construction. The method of five control points is suggested for imagery rectification introducing the algorithm offered by Prof. Ruan Wei (tong ji University, Shanghai). Image rectification software created on the basis of the above suggested algorithm can correct image deformation with required accuracy, is reliable and keeps advantages in flexibility. Experimental research on testing the applied technology has been executed using GeoEye imagery with Google Earth builder over the city of Vilnius. Orthophoto maps at the scales of 1:1000 and 1:500 are generated referring to the methodology of five control points. Reference data and rectification results are checked comparing with those received from processing digital aerial images using a digital photogrammetry approach. The image rectification process applying the investigated method takes a short period of time (about 4-5 minutes) and uses only five control points. The accuracy of the created models satisfies requirements for large scale mapping. Santrauka Didelės skiriamosios gebos skaitmeninių nuotraukų ir kosminių nuotraukų rektifikavimas miestams kartografuoti stambiuoju masteliu yra nauja technologija. Tai atliekant būtini tikslūs ir aiškiai matomi kontroliniai taškai. Skaitmeninės kosminės nuotraukos, gautos taikant plačiai žinomą programinį paketą Google Earth, gali būti naudojamos miestams kartografuoti dideliu tikslumu. Siūloma nuotraukas rektifikuoti Penkių kontrolinių taskų metodu pagal prof. Ruan Wei (Tong Ji universitetas, Šanchajus) algoritmą. Moksliniam eksperimentui pasirinkta Vilniaus GeoEye nuotrauka iš Google Earth. 1:1000 ir 1:500 mastelio ortofotografiniai žemėlapiai sudaromi Penkių kontrolinių taškų metodu. Rektifikavimo duomenys lyginami su skaitmeninių nuotraukų apdorojimo rezultatais, gautais skaitmeninės fotogrametrijos metodu. Nuotraukų rektifikavimas Penkių kontrolinių taskų metodu atitinka kartografavimo stambiuoju masteliu reikalavimus, sumažėja laiko sąnaudos. Резюме Ректификация цифровых и космических снимков высокой резолюции для крупномасштабного картографирования является новой технологией, требующей точных и четких контрольных точек. Цифровые космические снимки, полученные с использованием широкоизвестного программного пакета Google Earth, могут применяться для точного картографирования городов. Для ректификации снимков предложен метод пяти контрольных точек с применением алгоритма проф. Ruan Wei (Университет Tong Ji, Шанхай). Для научного эксперимента использован снимок города Вильнюса GeoEye из Google Earth. Ортофотографические карты в масштабе 1:1000 и 1:500 генерируются с применением метода пяти контрольных точек. Полученные результаты и данные ректификации сравниваются с результатами цифровых снимков, полученных с применением метода цифровой фотограмметрии. Ректификация снимков с применением метода пяти контрольных точек уменьшает временные расходы и удовлетворяет требования, предъявляемые к крупномасштабному картографированию.

Image deformation using modified Moving Least Squares with outlines

2017 ◽  
Author(s):  
Chong Yu ◽  
Xi Chen ◽  
Qiwei Xie ◽  
Guoqing Li ◽  
Lei Yin ◽  
...  
Keyword(s):  
Least Squares ◽  
Moving Least Squares ◽  
Image Deformation ◽  
Modified Moving Least Squares

Analysis of velocity interpolation schemes for image deformation methods in PIV

2008 ◽  
Vol 45 (2) ◽  
pp. 257-266 ◽  
Author(s):  
T. Astarita
Keyword(s):  
Image Deformation

A Contactless Palm Vein Recognition System Based on Principle Line SIFT

2013 ◽  
Vol 347-350 ◽  
pp. 3469-3472 ◽  
Author(s):  
Wei Wu ◽  
Sen Lin ◽  
Hui Song
Keyword(s):  
Traditional Method ◽  
Recognition System ◽  
Scale Invariant ◽  
Limited Effect ◽  
Image Deformation ◽  
Invariant Feature ◽  
Feature Transform ◽  
Vein Recognition ◽  
Palm Vein ◽  
Scale Invariant Feature

Compared with the traditional method of contact collection, contactless acquisition is the mainstream and trend of palm vein recognition. However, this method may lead to image deformation caused by no parallel of the palm plane and the sensor plane. In order to improve the limited effect of Scale Invariant Feature Transform (SIFT) about this problem, a better method of palm vein recognition which based on principle line SIFT is proposed. Based on the self-built database, this method is compared with the SIFT and other typical palm vein recognition methods, the experimental results show that our system can achieve the best performance.

Pathologies Prediction on Short ECG Signals with Focus on Feature Extraction Based on Beat Morphology and Image Deformation

2021 ◽  
Author(s):  
Jeffrey van Prehn ◽  
Svetoslav Ivanov ◽  
Georgi Nalbantov
Keyword(s):  
Feature Extraction ◽  
Image Deformation ◽  
Ecg Signals

The Research of 3D Projection Fusion Technology Based on Image Deformation

2015 ◽  
pp. 405-414
Author(s):  
Ma Yao ◽  
Liu Shufen ◽  
Han Lu
Keyword(s):  
Fusion Technology ◽  
Image Deformation

scholarly journals Sketch Based Image Deformation and Editing with Guaranteed Feature Correspondence

2012 ◽  
Vol 11 (1) ◽  
pp. 25-32
Author(s):  
Yaqiong Liu ◽  
Seah Hock Soon ◽  
Ying He ◽  
Juncong Lin ◽  
Jiazhi Xia
Keyword(s):  
Unit Circle ◽  
Delaunay Triangulation ◽  
Shape Deformation ◽  
Feature Correspondence ◽  
Good Correspondence ◽  
Image Deformation ◽  
Target Shape ◽  
Feature Lines ◽  
Complex Shapes ◽  
Correspondence Mapping

The establishment of a good correspondence mapping is a key issue in planar animations such as image morphing and deformation. In this paper, we present a novel mapping framework for animation of complex shapes. We firstly let the user extract the outlines of the interested object and target interested area from the input images and specify some optional feature lines, and then we generate a sparse delaunay triangulation mesh taking the outlines and the feature lines of the source shape as constraints. Then we copy the topology from the source shape to the target shape to construct a valid triangulation in the target shape. After that, each triangle of this triangular mesh is further segmented into a dense mesh patch. Each mesh patch is parameterized onto a unit circle domain. With such parametrization, we can easily construct a correspondence mapping between the source patches and the corresponding target patches. Our framework can work well for various applications such as shape deformation and morphing. Pleasing results generated by our framework show that the framework works well.

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