Latent semantic learning with time-series cross correlation analysis for video scene detection and classification

Cheng, Stone; Su, Jui-Yuan; Hsiao, Kuei‐Fang; Rashvand, Habib F.

doi:10.1007/s11042-015-2548-y

Cited by 6 publications

(2 citation statements)

References 39 publications

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“…The distortion of the spectrum will bring about highly random reflection spots (speckle) when the object is different; the speckles at different distances form different patterns and are received by the infrared receiver [19,20]. The depth image obtained by the infrared receiver is pixel-matched by the system processor and the color image obtained by the RGB camera to obtain a color image with depth information; the color camera obtains the color image, and the core component is the central processing unit chip, which is responsible for controlling other sensors [21,22]; for exam-ple, control the infrared transmitter to project the structure of the external light and at the same time receive the spot formed by the infrared light on the object through the CMOS image sensor and transmit it to the processor for processing to obtain the depth data and transmit it to the computer via USB [23,24]. Kinect somatosensory sensor is a device that combines a variety of data.…”

Section: Experimental Design Of Gymnastics Training System Based On Kinectmentioning

confidence: 99%

Role of Human Body Posture Recognition Method Based on Wireless Network Kinect in Line Dance Aerobics and Gymnastics Training

Zhou

2021

Wireless Communications and Mobile Computing

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With the rapid development of the information society, human body gesture recognition has become an important technology for human-computer interaction. This paper combines Kinect’s human bone monitoring technology with auxiliary gymnastics training. The gymnastics and dance training can correct students’ wrong movements in time through feedback and improve the training efficiency, so as to meet the needs of nature and harmony of human-machine interaction. In this paper, based on the wireless network Kinect, the human body posture recognition method and tracking technology are studied, and the joint point angle representation method based on the fixed axis is proposed, and the posture recognition method based on the joint point angle is improved, which can accurately recognize the human body posture. Aiming at the situation that the human joint points are occluded, the human joint point repair algorithm is improved. The algorithm is based on the proportion of human bone nodes and the characteristics of human motion, and based on geometric principles, it repairs the occluded points. The feasibility of the original joint point data, angle feature, and distance feature in expressing human behavior is analyzed through experiments, a standard gymnastics movement database is established, and new gymnastics movements can be entered at any time. A gymnastics auxiliary training system is designed, which can analyze and evaluate the exercises of the trainer from the joint point coordinates and the angle formed by the joints and provide the trainer with intuitive error correction prompts. The human body posture recognition method studied in this paper can accurately give the difference between the trainer’s movement and the standard movement, and the trainer can adjust the movement posture according to the prompts, improve the level of gymnastics, and achieve the purpose of auxiliary training. Experiments show that the algorithm model has an accuracy rate of 95.7% for human body posture recognition, and it plays a huge role in line dance aerobics and gymnastics training.

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Section: Experimental Design Of Gymnastics Training System Based On Kinectmentioning

confidence: 99%

Role of Human Body Posture Recognition Method Based on Wireless Network Kinect in Line Dance Aerobics and Gymnastics Training

Zhou

2021

Wireless Communications and Mobile Computing

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“…In another paper entitled BLatent Semantic Learning with Time-Series Cross Correlation Analysis for Video Scene Detection and Classification,^Cheng et al [4] presents a DTWbased video detection and classification based on the time-series cross correlation analysis with a latent semantic learning to generate the discriminative dynamic scene model for recognizing the event exhibited by a video sequence.…”

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confidence: 99%

Guest Editorial: Automated Big Data Analysis for Social Multimedia Network Environments

Lee

2016

Multimed Tools Appl

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Recently, with the rapid proliferation of various social network services, it has become very common for people to express their thoughts or opinions on various issues using brief comments. Popular issues include political events, new movies, commercial products, controversial bills and presidential candidates, to name a few. Even though such comments contain personal opinion or preference, they can collectively represent public opinions or trends. In practice, such public opinions or trends could provide very crucial information in many applications. For instance, it is quite important to know from user comments whether public opinion is positive or negative on a specific issue such as new regulation or policy. Another interesting example is to know in advance how big hit a new movie would be from user reviews or reactions on the movie trailer. However, to predict such thing is a very complicated task because there are so many factors that have influence on it. In many cases, such user comments are informal and sometimes unstructured, in that they contain many non-standard structures such as abbreviations, informal terms, emoticons, etc. Most previous works have focused on analyzing long documents such as blogs and hence they are not effective for very short and possibly informal SNS documents. Therefore, due to the abovementioned problems, the big data analysis using data mining and machine learning techniques should be considered in social network environment.We have finally selected nineteen manuscripts for this special issue after the first, second review processes. Each manuscript selected was blindly reviewed by at least three reviewers consisting of guest editors and external reviewers.The paper entitled BMulti-Scale Local Structure Patterns Histogram for Describing Visual Contents in Social Image Retrieval Systems,^by Baik et al. [1] proposes a local descriptor for personalized social image collections by utilizing twenty distinct structure patterns in salient edge maps at multiple scales. This allows both fine-grained and coarse-grained features to be

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A Scene Change Detection Framework Based on Deep Learning and Image Matching

Jiang

Kim

2018

Lecture Notes in Electrical Engineering

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Latent semantic learning with time-series cross correlation analysis for video scene detection and classification

Cited by 6 publications

References 39 publications

Role of Human Body Posture Recognition Method Based on Wireless Network Kinect in Line Dance Aerobics and Gymnastics Training

Role of Human Body Posture Recognition Method Based on Wireless Network Kinect in Line Dance Aerobics and Gymnastics Training

Guest Editorial: Automated Big Data Analysis for Social Multimedia Network Environments

A Scene Change Detection Framework Based on Deep Learning and Image Matching

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