Computer vision for interactive computer graphics

Freeman, William T.; Anderson, David; Beardsley, Paul; Dodge, Chris; Roth, Mark A.; Weissman, Craig D.; Yerazunis, William; Kage, Hiroshi; Kyuma, I.; Miyake, Y.; Tanaka, Kenichi

doi:10.1109/38.674971

Cited by 152 publications

(73 citation statements)

References 3 publications

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“…Freeman et al applied the idea of OH to create fast and simple hand interfaces [7]. The basic idea of OH is that hand pixels may vary in illumination, and pixel-bypixel difference leads to huge error in total.…”

Section: Orientation Histogrammentioning

confidence: 99%

“…Therefore, we have selected FD as a candidate. Freeman et al use Orientation Histogram which is a region-based global method, for several applications controlled by hand [7], [11]. Since there is no comparison of Orientation Histogram with others, and authors promote it in terms of both speed and recognition performance, we have also chosen it.…”

Section: Shape Representationsmentioning

confidence: 99%

“…Licsar and Sziranyi present another example that enables a user to manage presentation slides by hands [6]. Freeman et al let the users play games by their hands [7]. Nevertheless, there is no study comparing techniques employed in such a setup.…”

Section: Introductionmentioning

confidence: 99%

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Which Shape Representation Is the Best for Real-Time Hand Interface System?

Genç

Atalay

2009

Advances in Visual Computing

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Abstract. Hand is a very convenient interface for immersive human-computer interaction. Users can give commands to a computer by hand signs (hand postures, hand shapes) or hand movements (hand gestures). Such a hand interface system can be realized by using cameras as input devices, and software for analyzing the images. In this hand interface system, commands are recognized by analyzing the hand shapes and its trajectories in the images. Therefore, success of the recognition of hand shape is vital and depends on the discriminative power of the hand shape representation. There are many shape representation techniques in the literature. However, none of them are working properly for all shapes. While a representation leads to a good result for a set of shapes, it may fail in another one. Therefore, our aim is to find the most appropriate shape representation technique for hand shapes to be used in hand interfaces. Our candidate representations are Fourier Descriptors, Hu Moment Invariant, Shape Descriptors and Orientation Histogram. Based on widely-used hand shapes for an interface, we compared the representations in terms of their discriminative power and speed.

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Section: Orientation Histogrammentioning

confidence: 99%

Section: Shape Representationsmentioning

confidence: 99%

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Which Shape Representation Is the Best for Real-Time Hand Interface System?

Genç

Atalay

2009

Advances in Visual Computing

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“…Many researchers have proposed the use of hand tracking and gesture recognition as a powerful and natural interface for interaction with computers, game machines, and/or television sets [1]- [6]. In particular, bare hand tracking allows the user to control devices without attaching additional devices.…”

Section: Introductionmentioning

confidence: 99%

A Long-Range Touch Interface for Interaction with Smart TVs

Lee¹

2012

ETRI J

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A powerful interaction mechanism is one of the key elements for the success of smart TVs, which demand far more complex interactions than traditional TVs. This paper proposes a novel interface based on the famous touch interaction model but utilizes long-range bare hand tracking to emulate touch actions. To satisfy the essential requirements of high accuracy and immediate response, the proposed hand tracking algorithm adopts a fast colorbased tracker but with modifications to avoid the problems inherent to those algorithms. By using online modeling and motion information, the sensitivity to the environment can be greatly decreased. Furthermore, several ideas to solve the problems often encountered by users interacting with smart TVs are proposed, resulting in a very robust hand tracking algorithm that works superbly, even for users with sleeveless clothing. In addition, the proposed algorithm runs at a very high speed of 82.73 Hz. The proposed interface is confirmed to comfortably support most touch operations, such as clicks, swipes, and drags, at a distance of three meters, which makes the proposed interface a good candidate for interaction with smart TVs. Keywords: Smart TV, touch interface, bare hand tracking, human computer interaction. Manuscript received Oct. 19, 2011; revised Aug. 14, 2012; accepted Aug. 22, 2012. Jaeyeon Lee (phone: +82 42 860 5507, leejy@etri.re.kr), DoHyung Kim (dhkim008@etri.re.kr), Jaehong Kim (jhkim504@etri.re.kr ), Jae-il Cho (jicho@etri.re.kr), and Joochan Sohn (jcsohn@etri.re.kr) are with the IT Convergence Technology Research Laboratory, ETRI, Daejeon, Rep. of Korea.http://dx

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“…Computer vision techniques have recently become very popular in user interface research [7] Shared Space makes heavy use of computer vision techniques for tracking and registering virtual objects in the physical world [2].…”

Section: Shared Space Integrates a Number Of Novel Interface Technolomentioning

confidence: 99%