Virtual mouse vision based interface

Robertson, Paul; Laddaga, Robert; Kleek, Max Van

doi:10.1145/964474.964476

Cited by 12 publications

(18 citation statements)

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“…Paul [9] developed gesture based system for using their Kiosk interface. They trained their system to detect different hand signs out of which they used "thumbs up" sign for mouse movement and "fist" for clicking.…”

Section: International Journal Of Computer Applications (0975 -8887) mentioning

confidence: 99%

Project Mudra: Personalization of Computers using Natural Interface

Dave¹,

Bhumkar²,

Abraham³

et al. 2012

IJCA

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In recent years, the popularity for natural interfaces has experienced tremendous growth. Natural interfaces provide the computers or the so called machines with a sense of humanity. The basic knowledge required to understand and utilize a computer system is reduced to a minimal extent. There have been recent commercial developments in the area of natural interfaces, including the Microsoft XBOX Kinect and Nintendo WII. However, the capital cost of such a system remains very high.The primary intention of this paper is to design a technique to redesign every aspect of our interaction with the computer. It explores and develops an interface that helps simple computer systems to support gestural interface. We could utilize the low cost cameras available with the laptop or desktop to support detection of human gestures and multiple touch experiences, which would ultimately lead to the direct interaction of computers with humans. In such a system, the need for external input devices like mouse and keyboard could be eliminated. The paper discusses how such a system can be implemented, along with a brief description of the approach used.

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Section: International Journal Of Computer Applications (0975 -8887) mentioning

confidence: 99%

Project Mudra: Personalization of Computers using Natural Interface

Dave¹,

Bhumkar²,

Abraham³

et al. 2012

IJCA

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“…The color model was automatically initialized from hand detection. The system by Robertson et al [67] used a trained detector followed by optical flow tracking and was employed in a 'virtual mouse' application. Ike et al [37] presented a real-time system for gesture control that could detect three different hand poses independently in each frame.…”

Section: The Number Of State Parametersmentioning

confidence: 99%

A Vision-Based Remote Control

Stenger

Woodley

Cipolla

2010

Studies in Computational Intelligence

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This chapter presents a vision-based system for touch-free interaction with a display at a distance. A single camera is fixed on top of the screen and is pointing towards the user. An attention mechanism allows the user to start the interaction and control a screen pointer by moving their hand in a fist pose directed at the camera. On-screen items can be chosen by a selection mechanism. Current sample applications include browsing video collections as well as viewing a gallery of 3D objects, which the user can rotate with their hand motion. We have included an up-to-date review of hand tracking methods, and comment on the merits and shortcomings of previous approaches. The proposed tracker uses multiple cues, appearance, color, and motion, for robustness. As the space of possible observation models is generally too large for exhaustive online search, we select models that are suitable for the particular tracking task at hand. During a training stage, various off-the-shelf trackers are evaluated. From this data different methods of fusing them online are investigated, including parallel and cascaded tracker evaluation. For the case of fist tracking, combining a small number of observers in a cascade results in an efficient algorithm that is used in our gesture interface. The system has been on public display at conferences where over a hundred users have engaged with it.

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“…However, it struggles with rapid hand motion and skin coloured background objects. The system in [21] used a trained detector followed by optical flow tracking. Tracking based on optical flow alone has difficulties coping with rapid hand motion as well as moving background objects.…”

Section: Previous Workmentioning

confidence: 99%

“…Solutions that have previously been proposed include changing hand pose, finger or thumb extension and simply hovering over an icon for a short time period [4,6,9,11,16,21]. We have implemented these by training separate detectors, see detected by recording the hand motion over a sliding window of 20 frames and classifying this vector.…”

Section: Selection Mechanismsmentioning

confidence: 99%

“…To reduce the bias introduced by the finite number of frames (a failure close to the end may lead to a very short track) the last measurement before the end of the sequence is discarded if at least one tracking failures has occurred previously. The trackers that were compared against have been used in other hand tracking systems and include: local orientation correlation (LOC) [6], flocks of features tracking (FF) [11], optical flow tracking using templates on a regular grid (OF) and local feature tracking, KLT-tracker (KLT) [21], and boosted detection (BD) [9,11,17,19,21]. The performance of the individual components, the CM and NCC tracker, was also measured.…”

Section: Hand Tracking Experimentsmentioning

confidence: 99%

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AIDIA - Adaptive Interface for Display InterAction

Stenger

Woodley²,

Kim

et al. 2008

Procedings of the British Machine Vision Conference 2008

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This paper presents a vision-based system for interaction with a display via hand pointing. An attention mechanism based on face and hand detection allows users in the camera's field of view to take control of the interface. Face recognition is used for identification and customisation. The system allows the user to control the screen pointer by tracking their fist. On-screen items can be selected using one of four activation mechanisms. Current sample applications include browsing image and video collections as well as viewing a gallery of 3D objects. In experiments we demonstrate the performance of the vision components in challenging conditions and compare it to that of other systems.

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Virtual mouse vision based interface

Cited by 12 publications

References 0 publications

Project Mudra: Personalization of Computers using Natural Interface

Project Mudra: Personalization of Computers using Natural Interface

A Vision-Based Remote Control

AIDIA - Adaptive Interface for Display InterAction

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