Sketch recognition

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

Generic system for human-computer gesture interaction

Abstract: Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.

Gesture recognition system

Abstract: Gestures are a major form of human communication. Hence gestures are found to be an appealing way to interact with computers, as they are already a natural part of how we communicate. A primary goal of gesture recognition is to create a system which can identify specific human gestures and use them to convey information for device control and by implementing real time gesture recognition a user can control a computer by doing a specific gesture in front of a video camera linked to the computer. A primary goal of gesture recognition research is to create a system which can identify specific human gestures and use them to convey information or for device control. This project covers various issues like what are gesture, their classification, their role in implementing a gesture recognition system, system architecture concepts for implementing a gesture recognition system, major issues involved in implementing a simplified gesture recognition system, exploitation of gestures in experimental systems, importance of gesture recognition system, real time applications and future scope of gesture recognition system.The algorithm used in this project are Finger counting algorithm,X-Y axis(To recognize the thumb).

Advanced recognition techniques for human computer interaction

Abstract: Hand gestures are an important modality for human computer interaction (HCI) [1]. Compared to many existing interfaces, hand gestures have the advantages of being easy to use, natural, and intuitive. Successful applications of hand gesture recognition include computer games control [2], human-robot interaction [3], and sign language recognition [4], to name a few. Vision-based recognition systems can give computers the capability of understanding and responding to hand gestures. The aim of this technique is the proposal of a real time vision system for its application within visual interaction environments through hand gesture recognition, using general-purpose hardware and low cost sensors, like a simple personal computer and an USB web cam, so any user could make use of it in his office or home. The basis of our approach is a fast segmentation process to obtain the moving hand from the whole image, which is able to deal with a large number of hand shapes against different backgrounds and lighting conditions, and a recognition process that identifies the hand posture from the temporal sequence of segmented hands. The use of a visual memory (Stored database) allows the system to handle variations within a gesture and speed up the recognition process through the storage of different variables related to each gesture. A hierarchical gesture recognition algorithm is introduced to recognize a large number of gestures. Three stages of the proposed algorithm are based on a new hand tracking technique to recognize the actual beginning of a gesture using a Kalman filtering process, hidden Markov models and graph matching. Processing time is important in working with large databases. Therefore, special cares are taken to deal with the large number of gestures.

GLADDER: combining gesture and geometric sketch recognition

Abstract: Sketch recognition systems usually recognize strokes either as stylistic gestures or geometric shapes. Both techniques have their advantages. This paper presents a method for integrating gesture-based and geometric recognition techniques, significantly outperforming either technique on its own.

A Sketch Interface for Robust and Natural Robot Control

Abstract: In this paper, a novel approach for commanding mobile robots using a probabilistic multistroke sketch interface is presented. Drawing from prior work in handwriting recognition, sketches are modeled as a variable duration hidden Markov model, where the distributions on the states and transitions are learned from training data. A forward search algorithm is used to find the most likely sketch given the observations on the strokes, interstrokes, and gestures. A heuristic is implemented to discourage breadth-first search behavior, and is shown to greatly reduce computation time while sacrificing little accuracy. To avoid recognition errors, the recognized sketch is displayed to the user for confirmation; a rejection prompts the algorithm to search for and display the next most likely sketch. Upon confirmation of the recognized sketch, the robot executes the appropriate behaviors. A set of experiments was conducted in which operators controlled a single mobile robot in an indoor search-and-identify mission. Operators performed two missions using the proposed sketch interface and two missions using a more conventional point-and-click interface. On average, missions conducted using sketch control were performed as well as those using the point-and-click interface, and results from user surveys indicate that more operators preferred using sketch control.