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
Journal ArticleDOI
TL;DR: A survey on approaches which are based on Hidden Markov Models (HMM) for hand posture and gesture recognition for HCI applications is provided.
Abstract: Human hand recognition plays an important role in a wide range of applications ranging from sign language translators, gesture recognition, augmented reality, surveillance and medical image processing to various Human Computer Interaction (HCI) domains. Human hand is a complex articulated object consisting of many connected parts and joints. Therefore, for applications that involve HCI one can find many challenges to establish a system with high detection and recognition accuracy for hand posture and/or gesture. Hand posture is defined as a static hand configuration without any movement involved. Meanwhile, hand gesture is a sequence of hand postures connected by continuous motions. During the past decades, many approaches have been presented for hand posture and/or gesture recognition. In this paper, we provide a survey on approaches which are based on Hidden Markov Models (HMM) for hand posture and gesture recognition for HCI applications.

37 citations

Proceedings ArticleDOI
01 Nov 2010
TL;DR: A hand gesture detection and recognition system for Ethiopian Sign Language (ESL) has been proposed and Gabor Filter together with Principal Component Analysis (PCA) and Artificial Neural Network (ANN) is used for recognizing the ESL from extracted features and to translate into Amharic voice.
Abstract: Pattern recognition is very challenging multidisciplinary research area attracting researchers and practitioners. Gesture recognition is a specialized pattern recognition task with the goal of interpreting human gestures via mathematical models. One of the usages of gesture recognition is the sign language recognition which is the basic communication method between deaf people. Since there is lack of proficient sign language teachers at schools for the deaf, the teaching and learning process is remaining affected. A system is therefore required to overcome communication barriers facing the deaf community. So, in this paper, a hand gesture detection and recognition system for Ethiopian Sign Language (ESL) has been proposed. Gabor Filter (GF) together with Principal Component Analysis (PCA) has been used for extracting features from the digital images of hand gestures while Artificial Neural Network (ANN) is used for recognizing the ESL from extracted features and to translate into Amharic voice. The experimental results show that the system has produced recognition rate of 98.53%.

37 citations

Proceedings ArticleDOI
Bo Yu1
12 Jan 2003
TL;DR: This paper proposes a robust method for sketch recognition which combines the vertex detection and primitive shape approximation into a unified and incremental procedure which, by fully utilizing the visual features, can handle hybrid and smooth curves gracefully.
Abstract: Freehand sketching is a natural and powerful means of interpersonal communication. But to date, it still cannot be supported effectively by human-computer interface. In this paper, we propose a robust method for sketch recognition. It uses mean shift, a nonparametric technique which can delineate arbitrarily shaped clusters, as a pre-process to analyze the direction-curvature joint space and suppress the severe noise of sketched strokes. Furthermore, it combines the vertex detection and primitive shape approximation into a unified and incremental procedure which, by fully utilizing the visual features, can handle hybrid and smooth curves gracefully. Our method does not rely on any domain-specific knowledge, and therefore it can be easily integrated with other high-level applications

37 citations

Proceedings ArticleDOI
05 Aug 2007
TL;DR: SimuSketch, a sketch-based interface for Matlab's Simulink software package, is built and an evaluation has indicated that even novice users can effectively utilize the system to solve real engineering problems without having to know much about the underlying recognition techniques.
Abstract: A long standing challenge in pen-based computer interaction is the ability to make sense of informal sketches. A main difficulty lies in reliably extracting and recognizing the intended set of visual objects from a continuous stream of pen strokes. Existing pen-based systems either avoid these issues altogether, thus resulting in the equivalent of a drawing program, or rely on algorithms that place unnatural constraints on the way the user draws. As one step toward alleviating these difficulties, we present an integrated sketch parsing and recognition approach designed to enable natural, fluid, sketch-based computer interaction. The techniques presented in this paper are oriented toward the domain of network diagrams. In the first step of our approach, the stream of pen strokes is examined to identify the arrows in the sketch. The identified arrows then anchor a spatial analysis which groups the uninterpreted strokes into distinct clusters, each representing a single object. Finally, a trainable shape recognizer, which is informed by the spatial analysis, is used to find the best interpretations of the clusters. Based on these concepts, we have built SimuSketch, a sketch-based interface for Matlab's Simulink software package. An evaluation of SimuSketch has indicated that even novice users can effectively utilize our system to solve real engineering problems without having to know much about the underlying recognition techniques.

37 citations

Proceedings ArticleDOI
04 Jul 2016
TL;DR: In this paper the various techniques are discussed to recognize the hand gesture and the recognition of hand gesture will applicable in many fields.
Abstract: In the past years, the recognition of gesture feature has been glamoured attention as a natural human. The communication system can build the human relationships. The mode of communication will be verbal and non-verbal. The non-verbal communication is not only used for the physically challenged person, but also used in gaming, surveying, etc. There is no need of peripheral device to interact with the computer. In this paper the various techniques are discussed to recognize the hand gesture. In today's era, the Kinect depth data is the famous research for the identification of new fingers and the recognition of hand gesture. Finally, discuss the recognition of hand gesture will applicable in many fields.

37 citations


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