Vision based multi-user human computer interaction

Ueng, Shyh‐Kuang

doi:10.1007/s11042-015-3061-z

Cited by 8 publications

(6 citation statements)

References 10 publications

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“…There are seven papers [6,9,16,17,19] in the technology category of smart human machine interaction. These studies focus on the technique issue to realize a human computer interaction system for the specific application.…”

Section: Summary Of 2accepted Papersmentioning

confidence: 99%

“…Remote e-teaching systems for students [6,9,16] in the field of education and remote rehabilitation systems for patients in the field of home care [17] are two main smart human interaction interface applications. The 20th paper presented by Ueng and Chen [19] proposes a vision-based multi-user human computer interaction method for creating augmented reality user interfaces. The presented system in [19] is a smart HCI system, efficient, flexible, and practical for users with problems on using ordinary input devices.…”

Section: Summary Of 2accepted Papersmentioning

confidence: 99%

“…The 20th paper presented by Ueng and Chen [19] proposes a vision-based multi-user human computer interaction method for creating augmented reality user interfaces. The presented system in [19] is a smart HCI system, efficient, flexible, and practical for users with problems on using ordinary input devices.…”

Section: Summary Of 2accepted Papersmentioning

confidence: 99%

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Guest Editorial: Smart Multimedia Communication Technologies for New-Generation Artificial Intelligence Applications

Hsieh

2016

Multimed Tools Appl

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With the development of the Internet of thing (IoT) mechanism nowadays, the required techniques for artificial intelligence (AI)-related applications will be equipped with a crucial property, which is Bsmart.^Smart multimedia communication technologies are composed of two main technique categories: the smart multimedia processing technique class and the smart communication transmission technique class. These will be the necessity for constructing a new-generation AI application. The technical category of multimedia processing involves lots of types of techniques where pattern recognition, video (or image) processing, and human machine interaction (HCI) are three kernel technique types to establish an AI application under the regulation of the IoT mechanism. Video coding and decoding (codecs) techniques, media streaming techniques, and hardware-based techniques for enhancing media communication play important roles for establishing an efficient communication transmission channel between the user end device and the remote media handling server.BSmart multimedia communication technologies^associated with the new-generation AI application will absolutely be an evolution tendency for the development of multimedia and communication technologies. Following this thought line, we deeply believe that the appropriate term Bsmart^will be given to pattern recognition, video processing, human machine interaction, media streaming, and hardware-based media communication enhancement techniques for building up a smart multimedia communication system.The special issue, BSmart Multimedia Communication Technologies for New-Generation Artificial Intelligence Applications,^acts as a path breaker for exploring new-generation AI applications using multimedia communication technologies with intelligence. We totally received around 30 submissions, and the vast majority of all submissions are significant in Multimed Tools Appl (2016) 75:9665-9668

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Section: Summary Of 2accepted Papersmentioning

confidence: 99%

Section: Summary Of 2accepted Papersmentioning

confidence: 99%

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Guest Editorial: Smart Multimedia Communication Technologies for New-Generation Artificial Intelligence Applications

Hsieh

2016

Multimed Tools Appl

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“…The parameter b was decided by experiments carried out in Ueng and Chen. 7 The mean and the covariance matrix are retrieved from Wu and Ai. 6…”

Section: Gaussian Skin Color Modelmentioning

confidence: 99%

“…Figure 1 shows the improvement achieved by the proposed method in an HCI application. 7 The raw image is displayed in Figure 1(a). The skin regions detected using the approach of Yang et al 1 and Wu and Ai 6 are rendered in Figure 1(b), while the detected skin regions produced by the proposed method are illustrated in Figure 1(c).…”

Section: Introductionmentioning

confidence: 99%

Skin color model adaptation under varying lighting conditions

Ueng

Chang

2016

Advances in Mechanical Engineering

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Skin region detection is crucial for face recognition, hand tracking, and motion detection. In the detection process, a skin color model is usually required to confine the distribution of skin colors. However, skin color models are sensitive to lighting conditions. Skin segmentation under varying lighting conditions produces poor results. This article presents a skin detection procedure for human-computer interaction sessions under varying lighting conditions. The proposed method requests a skin sample from the user to estimate the color temperature of the light source. Then, the color temperature is used to correct the skin sample. At the subsequent step, the mean of the corrected skin sample is utilized to adapt the skin color model. Finally, the adapted skin color model is employed to segment skin regions in the video stream. Tests using the proposed method and some adaptive skin detection algorithms have been conducted. Statistical data show that the proposed method is superior to color constancy methods and the Gaussian mixture model in skin region segmentation. The proposed method improves the true positive rate by more than 13% in segmenting skin regions of a database. Its true positive rate is 20% better if real-life images are used as test data.

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Multi-activity 3D human motion recognition and tracking in composite motion model with synthesized transition bridges

Sun

Liu

et al. 2017

Multimed Tools Appl

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Vision based multi-user human computer interaction

Cited by 8 publications

References 10 publications

Guest Editorial: Smart Multimedia Communication Technologies for New-Generation Artificial Intelligence Applications

Guest Editorial: Smart Multimedia Communication Technologies for New-Generation Artificial Intelligence Applications

Skin color model adaptation under varying lighting conditions

Multi-activity 3D human motion recognition and tracking in composite motion model with synthesized transition bridges

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