Links between global and local shape perception, coloured backgrounds, colour discrimination, and non-verbal IQ

In this work a framework based on histogram of orientation of optical flow (HOOF) and local binary pattern from three orthogonal planes (LBP_TOP) is proposed for recognizing dynamic hand gestures. HOOF algorithm extracts local shape and dynamic motion information of gestures from image sequences and local descriptor LBP is extended to three orthogonal planes to create an efficient motion descriptor. These features are invariant to scale, translation, illumination and direction of motion. The performance of the new framework is tested in two different ways. The first one is by fusing the global and local features as one descriptor and the other is using features separately to train the multi class support vector machine. Performance analysis shows that the proposed approach produces better results for recognizing dynamic hand gestures when compared with state of the art methods

Download Full-text

Feature detection and tracking on geometric mesh data using a combined global and local shape model for face analysis

2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS) ◽

10.1109/btas.2015.7358761 ◽

2015 ◽

Cited By ~ 1

Author(s):

Shaun Canavan ◽

Lijun Yin

Keyword(s):

Feature Detection ◽

Shape Model ◽

Face Analysis ◽

Local Shape ◽

Geometric Mesh ◽

Detection And Tracking ◽

Feature Detection And Tracking ◽

Global And Local

Download Full-text

Categorical Local-Shape Perception

Perception ◽

10.1068/p250095 ◽

1996 ◽

Vol 25 (1) ◽

pp. 95-107 ◽

Cited By ~ 15

Author(s):

Pascal Mamassian ◽

Daniel Kersten ◽

David C Knill

Keyword(s):

Shape Perception ◽

Simple Object ◽

Local Shape ◽

Parabolic Curve ◽

Shape Characteristic ◽

Hyperbolic Points ◽

Hyperbolic Saddle ◽

Potential Representation

How well do observers perceive the local shape of an object from its shaded image? This problem was addressed by first deriving a potential representation of local solid shape. The descriptor of local shape, called shape characteristic, provides a viewpoint-independent continuum between hyperbolic (saddle-shaped) and elliptic (egg-shaped) points. The ability of human observers to make categorical judgments of local solid shape was then studied. This question was investigated by using a smooth ‘croissant’, a simple object made of two connected regions of elliptic and hyperbolic points. Observers decided whether the surface was locally elliptic or hyperbolic at various points on the object. The task was natural, and the observers could reliably partition the shaded image of the object into two regions, one elliptic and one hyperbolic. The ability of observers to perform this partition shows that they can, at least implicitly, localize the parabolic curves on a surface. This ability to locate the parabolic curve could in turn be exploited for other purposes, for instance to segment an object into its parts.

Download Full-text

Shape-Based Image Retrieval Using Combining Global and Local Shape Features

2009 2nd International Congress on Image and Signal Processing ◽

10.1109/cisp.2009.5304693 ◽

2009 ◽

Cited By ~ 15

Author(s):

Yanyan Wu ◽

Yiquan Wu

Keyword(s):

Image Retrieval ◽

Shape Features ◽

Local Shape ◽

Global And Local

Download Full-text

Multi-Sensor Face Registration Based on Global and Local Structures

Applied Sciences ◽

10.3390/app9214623 ◽

2019 ◽

Vol 9 (21) ◽

pp. 4623 ◽

Cited By ~ 3

Author(s):

Li ◽

Dong ◽

Lu ◽

Lou ◽

Zhou

Keyword(s):

Feature Point ◽

Shape Descriptors ◽

Point Sets ◽

Local Shape ◽

Local Structures ◽

Face Images ◽

Local Shape Descriptors ◽

Student’S T ◽

Global And Local ◽

Geometrical Relationship

The work reported in this paper aims at utilizing the global geometrical relationship and local shape feature to register multi-spectral images for fusion-based face recognition. We first propose a multi-spectral face images registration method based on both global and local structures of feature point sets. In order to combine the global geometrical relationship and local shape feature in a new Student’s t Mixture probabilistic model framework. On the one hand, we use inner-distance shape context as the local shape descriptors of feature point sets. On the other hand, we formulate the feature point sets registration of the multi-spectral face images as the Student’s t Mixture probabilistic model estimation, and local shape descriptors are used to replace the mixing proportions of the prior Student’s t Mixture Model. Furthermore, in order to improve the anti-interference performance of face recognition techniques, a guided filtering and gradient preserving image fusion strategy is used to fuse the registered multi-spectral face image. It can make the multi-spectral fusion image hold more apparent details of the visible image and thermal radiation information of the infrared image. Subjective and objective registration experiments are conducted with manual selected landmarks and real multi-spectral face images. The qualitative and quantitative comparisons with the state-of-the-art methods demonstrate the accuracy and robustness of our proposed method in solving the multi-spectral face image registration problem.

Download Full-text

Surface Parameterization for the Shape Analysis of Tube-Like Objects

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.239-240.694 ◽

2012 ◽

Vol 239-240 ◽

pp. 694-699

Author(s):

Li Feng Yao ◽

Jian Fei Ouyang ◽

Xiang Ma

Keyword(s):

Shape Analysis ◽

Shape Variation ◽

Conduction Model ◽

Shape Information ◽

Local Shape ◽

3D Objects ◽

Surface Parameterization ◽

Sample Shape ◽

Latitude Circle ◽

Global And Local

In bio-medicine and other fields, shape analysis is very important for diagnosis of diseases and prediction of shape variation. This paper focuses on the surface parameterization of tube-like 3D objects to obtain and analyze shape information from a sample shape, including its size and the shape variation between different samples. It can well represent the global and local shape information for statistical analysis and for the construction of Medial Shape Model. Firstly, we extract the axis curve of the object by a heat conduction model. Secondly, we obtain the latitude circles by using the normal planes to cross the surface. Then we get the final parameterized surface with quad-dominant meshes by registering the points of single latitude circle and between different circles through coordinate transformation and alignment. Subsequently, we apply the approach to parameterization of a rib bone.

Download Full-text