113 Slices
Medium 9781601323248

Continuous Gesture Recognition Using Hidden Markov Models

Hamid R. Arabnia, Leonidas Deligiannidis Joan Lu, Fernando G. Tinetti, Jane You, George Jandieri, Gerald Schaefer, and Ashu M.G. Solo CSREA Press PDF

442

Int'l Conf. IP, Comp. Vision, and Pattern Recognition | IPCV'14 |

CONTINUOUS GESTURE RECOGNITION USING HIDDEN MARKOV MODELS

Joceli Mayer and Vinicius Breda

Digital Signal Processing Laboratory

Federal University of Santa Catarina - Florianopolis - SC - Brazil joceli.mayer@lpds.ufsc.br

ABSTRACT

2. THE PROPOSED APPROACH

This work presents an algorithm for recognizing gestures in videos where the actions are executed continuously without pause between them and can be performed with one or both hands. We employ Hidden Markov Models (HMM) for modeling gestures as this technique has been applied successfully in speech and character recognition, We investigate the performance for a set of 26 visual descriptors extracted from the hands after a region segmentation based on normalized quadrants. Recognition are performed by adapting the Hidden Markov Models Toolkit (HTK) and achieve a recognition rate of 91.28% for a set of 21 phrases each composed of 4 gestures from a dictionary of 15 gestures from the Brazilian sign language (LIBRAS).

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Medium 9781601323248

A Hole-Filling Approach Based on Morphological Operation for Stereoscopic Image Generation

Hamid R. Arabnia, Leonidas Deligiannidis Joan Lu, Fernando G. Tinetti, Jane You, George Jandieri, Gerald Schaefer, and Ashu M.G. Solo CSREA Press PDF

Int'l Conf. IP, Comp. Vision, and Pattern Recognition | IPCV'14 |

145

A Hole-Filling Approach Based on Morphological

Operation for Stereoscopic Image Generation

Chyuan-Huei Thomas Yang, Yen-Ting Hsu, Wen-Chieh, Chou

Department of Information Management, Hsuan Chuang University, Hsin Chu, Taiwan

Abstract - Apply the stereoscopic image generation from 2D to 3D conversion depth image based rendering (DIBR) technique it is 2D view to multi-angle virtual view by the single depth image. We develop a stereoscopic image generation method from one-view color image and its corresponding depth information. The DIBR firstly does the preprocessing of the depth image by using the smooth filter, which sharpens the discontinuous depth changes as well as to smooth the neighboring depth of similar color and also detain noises from appearing on the warped images. The occlusion regions are applied the morphological operations on the depth image with the background depth levels to keep the depth structure. With depth-guided exemplar-based image inpainting combines the color gradient to preserve the image structure in the restored regions.

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Medium 9781601323248

Session - Biometrics + Face Recognition, Expression Detection, Human Detection

Hamid R. Arabnia, Leonidas Deligiannidis Joan Lu, Fernando G. Tinetti, Jane You, George Jandieri, Gerald Schaefer, and Ashu M.G. Solo CSREA Press PDF
Medium 9781601323248

Preliminary study on the hand clapping action recognition based on the Leap Motion Controller

Hamid R. Arabnia, Leonidas Deligiannidis Joan Lu, Fernando G. Tinetti, Jane You, George Jandieri, Gerald Schaefer, and Ashu M.G. Solo CSREA Press PDF

542

Int'l Conf. IP, Comp. Vision, and Pattern Recognition | IPCV'14 |

Preliminary study on the hand clapping action recognition based on the Leap Motion Controller

Jin-Woo Jung1, Hyeseong Lee2 , Jung-Soo Park3 and Yong-One Cho4

1,2,3,4

Department of Computer Science and Engineering, Dongguk University, Seoul, Korea

1

Email : jwjung@dongguk.edu (corresponding author)

Abstract - In this paper, we propose a method of recognizing human hand clapping action based on the Leap Motion

Controller. Basic hand clapping is a kind of simple but somewhat fast periodic hand action. By the inevitable occlusion of two hands, fast speed of hand motion, and its neighboring noisy data, it is not easy to be recognized either by vision sensors or by sound sensors.

Leap Motion Controller (LMC) is one of the most advanced and low-priced devices which can be used to detect the detailed motion of multiple moving objects in some restricted range. By the fast and accurate hand trajectory data from

Leap Motion Controller, we can predict the relative position of two palms more accurately. And, by using the prior knowledge about basic hand clapping action sequence, LMCbased hand clapping recognizer has been developed. The average success ratio is 86.11% with the three different test users and 240 tests per each user.

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Medium 9781601323248

Improving Performance using both of Correlation and Absolute Difference on Similar Play Estimation

Hamid R. Arabnia, Leonidas Deligiannidis Joan Lu, Fernando G. Tinetti, Jane You, George Jandieri, Gerald Schaefer, and Ashu M.G. Solo CSREA Press PDF

Int'l Conf. IP, Comp. Vision, and Pattern Recognition | IPCV'14 |

289

Improving Performance using both of Correlation and

Absolute Difference on Similar Play Estimation

Kyota Aoki and Ryo Aita

Graduate school of Engineering, Utsunomiya University, Utsunomiya, Tochigi, JAPAN

Abstract - Plays in sports are described as the motions of players. This paper proposes the similar play retrieving method based on the motion compensation vector in MPEG sports videos. In MPEG videos, there are motion compensation vectors. Using the motion compensation vectors, we don’t need to estimate the motion vectors between adjacent frames. This work uses the 1D degenerated descriptions of each motion image between 2 adjacent frames. Connecting the 1D degenerated descriptions on time direction, we have the spacetime image. This space-time image describes a sequence of frames as a 2-dimensional image. Using this space-time image, this work shows the performance using both of the correlation and the absolute difference to retrieve a small number of plays in a huge number of frames based on a single template play.

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