scispace - formally typeset
Search or ask a question
Topic

Sketch recognition

About: Sketch recognition is a research topic. Over the lifetime, 1611 publications have been published within this topic receiving 40284 citations.


Papers
More filters
01 Jan 2014
TL;DR: This chapter focuses on feature selection and classification of multi-feature patterns and a detailed review of hand gesture recognition algorithms and techniques.
Abstract: This chapter focuses on feature selection and classification of multi-feature patterns. Micro array based cancer classification and image based face recognition are discussed. A detailed review of hand gesture recognition algorithms and techniques is included. The hand gesture recognition algorithms are surveyed by classifying them into three categories (a) hidden Markov model based methods, (b) neural net- work and learning based methods, and (c) the other methods. A list of available hand gesture databases is provided.
Proceedings ArticleDOI
01 Sep 2007
TL;DR: The learning capability of a human gesture recognition method based on computational intelligence is discussed, which is composed of image processing for human face and hand detectionbased on a steady-state genetic algorithm, an extraction method for human hand motion based on a fuzzy spiking neural network, and an unsupervised classification method forhuman hand motionBased on a self- organizing map.
Abstract: Recently, various types of human-friendly robot have been developed. Such robots should perform voice recognition, gesture recognition, and others. This paper discusses the learning capability of a human gesture recognition method based on computational intelligence. The proposed method is composed of image processing for human face and hand detection based on a steady-state genetic algorithm, an extraction method for human hand motion based on a fuzzy spiking neural network, and an unsupervised classification method for human hand motion based on a self- organizing map. We show several experimental results and discuss their effectiveness.
Journal Article
TL;DR: This research introduces a new approach using cellular technology for solving various problems of processing and pattern recognition images that are invariant to the orientation, scale, and dynamic changes in real time.
Abstract: Supervised learning has been considered as a hot topic as it is used in different fields that can exploit the advantages of artificial intelligence. This research introduces a new approach using cellular technology for solving various problems of processing and pattern recognition images that are invariant to the orientation, scale, and dynamic changes in real time. On the basis of the notion of geometric type solved the problem of information selection elements in the image recognition of shapes, lines and laser processing of personal identification for handwritten text. Keywords: cellular technology, pattern recognition, figures recognition, neural network
Book ChapterDOI
Dan Xiao1
01 Jul 2015
TL;DR: This paper compared three different algorithms for labeling each drawn stroke as being a particular component in the generic model and shows that K-means classifier yields better results than the other two.
Abstract: Compared to free sketch, gesture-based sketch recognition can achieve high accuracy by requiring the user to learn a particular drawing style in order for shapes to be recognized. In this case, choosing an appropriate classifier is quite critical. This paper compared three different algorithms for labeling each drawn stroke as being a particular component in the generic model. Our statistic shows that K-means classifier yields better results than the other two and we test that by applying this classifier to rocket sketches.
Proceedings ArticleDOI
26 Aug 2004
TL;DR: In this paper, a biology vision inspired model is proposed to realize rotation invariant recognition, which is expressed in three aspects: Gabor filters pair like complex cell, singularities and memory trace.
Abstract: Invariant recognition is a traditional challenge in computer vision. A biology vision inspired model is proposed to realize rotation invariant recognition. Neurobiological plausibility of the model is expressed in three aspects: Gabor filters pair like complex cell, singularities and memory trace. Recurrent connections decrease distinction of complex cells leading to emergence of singularities. Memory trace extracts correlations of different views of the same objects from continual sequences, and therefore is fit for performing recognition tasks. We testify efficacy of the model by benchmark recognition problem.

Network Information
Related Topics (5)
Feature (computer vision)
128.2K papers, 1.7M citations
84% related
Object detection
46.1K papers, 1.3M citations
83% related
Feature extraction
111.8K papers, 2.1M citations
82% related
Image segmentation
79.6K papers, 1.8M citations
81% related
Convolutional neural network
74.7K papers, 2M citations
80% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202326
202271
202130
202029
201946
201827