Results 171 to 180 of about 5,849,321 (239)

Hand shape recognition

Optics & Laser Technology, 2000
Automated hand shape recognition has been studied over the past decade and some commercial systems have been developed. Despite these advances, there is not much open public literature discussing the hand shape verification research. This study proposes a method by using quadtree techniques, which are able to recognize the hand shape image within an ...
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Recognition of shape parts using shape geodesies

2015 International Conference on Image Processing Theory, Tools and Applications (IPTA), 2015
In this paper, we address the problem of shape part recognition. For this purpose, we define a robust distance between shape parts based on geodesics in the shape space. The proposed distance uses an elastic shape matching to handle elastic deformations and compare shape parts locally.
Mayss'aa Merhy, Abdesslam Benzinou, Kamal Nasreddine, Mohamad Khalil, Ghaleb Faour   +4 more
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Texture and Shape Biased Two-Stream Networks for Clothing Classification and Attribute Recognition

Computer Vision and Pattern Recognition, 2020
Clothes category classification and attribute recognition have achieved distinguished success with the development of deep learning. People have found that landmark detection plays a positive role in these tasks.
Yuwei Zhang, Peng Zhang, C. Yuan, Zhi Wang   +3 more
semanticscholar   +1 more source

“Shape theory” and pattern recognition

Pattern Recognition, 1983
Abstract The contribution of this article consists of giving an insight into the topological Theory of Shape and hints upon its application to Shape Analysis and Pattern Recognition in general. It states this theory's impact and limitations when applied to Pattern Recognition and lists some open research problems in this field.
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Shape space object recognition

SPIE Proceedings, 2001
In this paper, we describe a shape space based approach for invariant object representation and recognition. In this approach, an object and all its similarity transformed versions are identified with a single point in a high-dimensional manifold called the shape space.
Xiao Zhang, Jun Zhang, Gilbert G. Walter, A. Hamid Krim   +3 more
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Shape based leaf recognition

2013 21st Signal Processing and Communications Applications Conference (SIU), 2013
Humans carry out object recognition as a very primitive task. However, knowing all the detailed information regarding an object is mostly not possible. Therefore, object recognition and linking the object to associated data is a popular research area. In this study, we have measured leaf recognition performances of different feature and data sets using
C. Sari, C. B. Akgul, B. Sankur
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Shape-based fish recognition via shape space

2015 23rd European Signal Processing Conference (EUSIPCO), 2015
Automatic fish recognition is a recent research work which is needed to assist marine scientists. Among most discriminative features, the fish outline is very efficient for fish recognition. In a previous work, we proposed a method for pattern recognition (classification and retrieval) based on signal registration and shape geodesics. In this paper, we
Kamal Nasreddine, Abdesslam Benzinou
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Indexing Shapes for Recognition

SPIE Proceedings, 1987
The visual features most important for object recognition are those having to do with the shape of an object. In one approach to recognition The image is decomposed an image into a set of relatively simple shapes (parts) and predicates that describe these parts and the relationships between them. Recognition is a matter of matching this parts-relations
Gene R. Gindi, Donald H. Delorie, Jr.
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Shape Recognition Methods Used for Complex Polygonal Shape Recognition

2014
Two new algorithms, optimal and sub-optimal solution algorithm, for shape recognition using geometric calculations are proposed. They are mode-based, which means that shape from the data base which is considered as a model is compared with another shape extracted from the sequence of images, such as, for example, a moving object.
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SubUNets: End-to-End Hand Shape and Continuous Sign Language Recognition

IEEE International Conference on Computer Vision, 2017
We propose a novel deep learning approach to solve simultaneous alignment and recognition problems (referred to as “Sequence-to-sequence” learning). We decompose the problem into a series of specialised expert systems referred to as SubUNets.
Necati Cihan Camgöz, Simon Hadfield, Oscar Koller, R. Bowden   +3 more
semanticscholar   +1 more source