• Electronics and Telecommunications Trends
• /
• v.34 no.3
• /
• pp.34-42
• /
• 2019

This study introduces artificial intelligence (AI) techniques for video generation. For an effective illustration, techniques for video generation are classified as either semi-automatic or automatic. First, we discuss some recent achievements in semi-automatic video generation, and explain which types of AI techniques can be applied to produce films and improve film quality. Additionally, we provide an example of video content that has been generated by using AI techniques. Then, two automatic video-generation techniques are introduced with technical details. As there is currently no feasible automatic video-generation technique that can generate commercial videos, in this study, we explain their technical details, and suggest the future direction for researchers. Finally, we discuss several considerations for more practical automatic video-generation techniques.

• Nuclear Engineering and Technology
• /
• v.54 no.4
• /
• pp.1153-1160
• /
• 2022

The application of video processing techniques are useful for the safety of nuclear power plants by tracking the people online on video to estimate the dose received by staff during work in nuclear plants. Nuclear reactors remotely visually controlled to evaluate the plant's condition using video processing techniques. Internal reactor components should be frequently inspected but in current scenario however involves human technicians, who review inspection videos and identify the costly, time-consuming and subjective cracks on metallic surfaces of underwater components. In case, if any frame of the inspection video degraded/corrupted/missed due to noise or any other factor, then it may cause serious safety issue. The problem of missing/degraded/corrupted video frame estimation is a challenging problem till date. In this paper a systematic literature review on video processing techniques is carried out, to perform their suitability analysis for NPP applications. The limitation of existing approaches are also identified along with a roadmap to overcome these limitations.

• Korean Journal of Geomatics
• /
• v.3 no.1
• /
• pp.23-32
• /
• 2003

Rigorous sensor and dynamic modeling techniques are required if spatial information is to be accurately extracted from video imagery. First, a mathematical model for an uncalibrated video camera and a description of a bundle adjustment with added parameters, for purposes of general block triangulation, is presented. This is followed by the application of invariance-based techniques, with constraints, to derive initial approximations for the camera parameters. Finally, dynamic modeling using the Kalman Filter is discussed. The results of various experiments with real video imagery, which apply the developed techniques, are given.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.10 no.1
• /
• pp.45-53
• /
• 1998

Video monitoring techniques and their applications to beaches were reviewed. The recent development of video hardware and image process made it possible to measure shoreline changes, sandbar morphology, wave runup, swash motion, and so on using video camaras. Especially, quantitative information from the video image can be obtained by digitization of image, rectification procedure, and image process. Using video monitoring techniques, measurements can be made at much lower cost and for long periods of time compared to the traditional measurement techniques, although these techniques are of lower accuracy and provide only indirect information on the land and water surface.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.40 no.1
• /
• pp.96-102
• /
• 2003

Video copy detection is a complementary approach to watermarking. As opposed to watermarking, which relies on inserting a distinct pattern into the video stream, video copy detection techniques match content-based signatures to detect copies of video. Existing typical content-based copy detection schemes have relied on image matching. This paper proposes two new sequence matching techniques for copy detection and compares the performance with color techniques that is the existing techniques. Motion, intensity and color-based signatures are compared in the context of copy detection. Comparison of experimental results are reported on detecting copies of movie clips.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.6 no.6
• /
• pp.931-936
• /
• 2002

By emphasize and enhance security in encryption of same viewdata in this research, constructed video conference system that apply real time video encryption techniques that confidentiality and integrity aspect are emphasized than video conference system that depend on existent user certification techniques. Sender's image transmits Vernam's encryption process to listener by packet. Listener can display image through image's decipher process and uncompress after unite receiving transmited image. This time, solved transmission speed delay problem by video's real time encryption using Vernam's algorithm that encryption and the decipher speed are fast. Simplification problem of Vernam algorithm wished to solve Session Key that use security Key that is used encipherment and decipher in channel between Client and Server using RSA algorithm.

• Journal of Korea Multimedia Society
• /
• v.25 no.4
• /
• pp.583-599
• /
• 2022

Although the object detection accuracy with a single image has been significantly improved with the advance of deep learning techniques, the detection accuracy for pig monitoring is challenged by occlusion problems due to a complex structure of a pig room such as food facility. These detection difficulties with a single image can be mitigated by using a video data. In this research, we propose a method in pig detection for video monitoring environment with a static camera. That is, by using both image processing and deep learning techniques, we can recognize a complex structure of a pig room and this information of the pig room can be utilized for improving the detection accuracy of pigs in the monitored pig room. Furthermore, we reduce the execution time overhead by applying a pruning technique for real-time video monitoring on an embedded board. Based on the experiment results with a video data set obtained from a commercial pig farm, we confirmed that the pigs could be detected more accurately in real-time, even on an embedded board.

• Journal of Broadcast Engineering
• /
• v.7 no.2
• /
• pp.79-87
• /
• 2002

The fast advances in digital video processing and multimedia processing technology over the last decade enabled various non-linear video browsing techniques. Based on the machine-understanding of the video content, non-linear video brows ing interfaces such as key-frame based content summarization have been introduced. The key-frame based user interfaces, such as storyboard or table of content, however, are still very hard for conventional TV users to use, and are very hard to implement without the service providers providing additional information for the construction of the key-frame based interfaces. In this paper, non-linear video browsing techniques, which not only overcome previously described drawbacks but also are easy-to-use, and real-time video indexing technology to support the proposed browsing techniques are proposed. The structure-based skipping and skimming help users easily find interesting scene and understand the content in a very short time, using real-time video indexing technology.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2007.08b
• /
• pp.1231-1234
• /
• 2007

This paper presents the overview of 3D video processing technologies for 3DTV such as 3D content generation, 3D video codec and video processing techniques for 3D displays. Some experimental results for 3D contents generation are shown in 3D mixed reality and 2D/3D conversion.

• IEIE Transactions on Smart Processing and Computing
• /
• v.4 no.2
• /
• pp.110-114
• /
• 2015

This paper reports a novel object-detection technique in video sequences. The proposed algorithm consists of detection of objects in illuminated and occluded videos by using object features and a neural network technique. It consists of two functional modules: region-based object feature extraction and continuous detection of objects in video sequences with region features. This scheme is proposed as an enhancement of the Lowe's scale-invariant feature transform (SIFT) object detection method. This technique solved the high computation time problem of feature generation in the SIFT method. The improvement is achieved by region-based feature classification in the objects to be detected; optimal neural network-based feature reduction is presented in order to reduce the object region feature dataset with winner pixel estimation between the video frames of the video sequence. Simulation results show that the proposed scheme achieves better overall performance than other object detection techniques, and region-based feature detection is faster in comparison to other recent techniques.