• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.691-701
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• 2010

We propose a haptic rendering technology for touchable video. Our touchable video technique allows users for feeling the sense of touch while probing directly on 2D objects in video scenes or manipulating 3D objects brought out from video scenes using haptic devices. In our technique, a server sends video and haptic data as well as the information of 3D model objects. The clients receive video and haptic data from the server and render 3D models. A video scene is divided into small grids, and each cell has its tactile information which corresponds to a specific combination of four attributes: stiffness, damping, static friction, and dynamic friction. Users can feel the sense of touch when they touch directly cells of a scene using a haptic device. Users can also examine objects by touching or manipulating them after bringing out the corresponding 3D objects from the screen. Our touchable video technique proposed in this paper can lead us to feel maximum satisfaction the haptic-audio-vidual effects directly on the video scenes of movies or home-shopping video contents.

• ETRI Journal
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• v.31 no.1
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• pp.1-9
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• 2009

Frequency domain analysis is a fundamental procedure for understanding the characteristics of visual data. Several studies have been conducted with 2D videos, but analysis of stereoscopic 3D videos is rarely carried out. In this paper, we derive the Fourier transform of a simplified 3D video signal and analyze how a 3D video is influenced by disparity and motion in terms of temporal aliasing. It is already known that object motion affects temporal frequency characteristics of a time-varying image sequence. In our analysis, we show that a 3D video is influenced not only by motion but also by disparity. Based on this conclusion, we present a temporal anti-aliasing filter for a 3D video. Since the human process of depth perception mainly determines the quality of a reproduced 3D image, 2D image processing techniques are not directly applicable to 3D images. The analysis presented in this paper will be useful for reducing undesirable visual artifacts in 3D video as well as for assisting the development of relevant technologies.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.125-135
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• 1997

This paper is concerned with realistic mainpulation of content in video sequences. Manipulation of content in video sequences is one of the content-based functionalities for MPEG-4 Visual standard. We present an approach to synthesizing video sequences by using the intermediate outputs of three-dimensional (3D) motion and depth analysis. For concreteness, we focus on video showing 3D motion of an observer relative to a scene containing planar runways (or roads). We first present a simple runway (or road) model. Then, we describe a method of identifying the runway (or road) boundary in the image using the Point of Heading Direction (PHD) which is defined as the image of, the ray along which a camera moves. The 3D motion of the camera is obtained from one of the existing 3D analysis methods. Then, a video sequence containing a runway is manipulated by (i) coloring the scene part above a vanishing line, say blue, to show sky, (ii) filling in the occluded scene parts, and (iii) overlaying the identified runway edges and placing yellow disks in them, simulating lights. Experimental results for a real video sequence are presented.

• Journal of Korea Multimedia Society
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• v.22 no.6
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• pp.655-664
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• 2019

In this paper, we propose a novel way of combining multiple deep convolutional neural network (DCNN) architectures which work well for accurate video face identification by adopting a serial combination of 3D and 2D DCNNs. The proposed method first divides an input video sequence (to be recognized) into a number of sub-video sequences. The resulting sub-video sequences are used as input to the 3D DCNN so as to obtain the class-confidence scores for a given input video sequence by considering both temporal and spatial face feature characteristics of input video sequence. The class-confidence scores obtained from corresponding sub-video sequences is combined by forming our proposed class-confidence matrix. The resulting class-confidence matrix is then used as an input for learning 2D DCNN learning which is serially linked to 3D DCNN. Finally, fine-tuned, serially combined DCNN framework is applied for recognizing the identity present in a given test video sequence. To verify the effectiveness of our proposed method, extensive and comparative experiments have been conducted to evaluate our method on COX face databases with their standard face identification protocols. Experimental results showed that our method can achieve better or comparable identification rate compared to other state-of-the-art video FR methods.

• Journal of Broadcast Engineering
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• v.8 no.4
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• pp.452-464
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• 2003

In this paper, a multi-view 3D video processor was designed and implemented with several FPGAs for real-time applications. The 3D video processor receives 2D images from cameras (up to 16 cameras) and converts then to 3D video format for space-multiplexed 3D display. It can cope with various arrangements of 3D camera systems (or pixel arrays) and resolutions of 3D display. Tn order to verify the functions of 3D video Processor. some evaluation-board were made with five FPGAs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.943-950
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• 2011

In this paper, we presented an attention measurement method in 2D and 3D image/video to be applied for image and video retargeting and compressive processing. 2D attention is derived from the three main components, intensity, color, and orientation, while depth information is added for 3D attention. A rarity-based attention method is presented to obtain more interested region or objects. Displaced depth information is matched to attention probability in distorted stereo images and finally a stereo distortion predictor is designed by integrating low-level HVS responses. As results, more efficient attention scheme is developed from the conventional methods and performance is proved by applying for video retargeting.

• Journal of Korea Game Society
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• v.13 no.3
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• pp.5-18
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• 2013

This study analyzed the effect by comparing it with 2D game using playtest experimental treatment methodology to verify the video effect, materiality and fatigue effect of 3D video game. First, for the hypothesis to verify the difference of video experience of users for 3D and 2D games, visual clarity was rejected, but materiality, tangibility and presence hypotheses were all accepted. Second, it was shown that there was no difference in eye fatigue and physical fatigue in 3D and 2D games. It was different from results of existing research which claimed that fatigue occurred due to video distortion occurring in 3D video and fatigue inducing factors. Third, the results of measurement of changes in brain wave occurring in the course of playing 3D and 2D games showed that there was no difference in average amplitude of EEG alpha wave, but EEG beta wave occurred in higher amplitude. This study proved the cerebral physiological change and difference in the process of experience to use 3D video game by complementing the methodology in measurement in EEG brain wave in the traditional experimental method.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.1-13
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• 2012

3D video is regarded as the next generation contents in numerous applications. The 2D-to-3D video conversion technologies are strongly required to resolve a lack of 3D videos during the period of transition to the full ripe 3D video era. In 2D-to-3D conversion methods, after the depth image of each scene in 2D video is estimated, stereoscopic video is synthesized using DIBR (Depth Image Based Rendering) technologies. This paper proposes a novel depth fusion algorithm that integrates multiple depth cues contained in 2D video to generate stereoscopic video. For the proper depth fusion, it is checked whether some cues are reliable or not in current scene. Based on the result of the reliability tests, current scene is classified into one of 4 scene types and scene-adaptive depth fusion is applied to combine those reliable depth cues to generate the final depth information. Simulation results show that each depth cue is reasonably utilized according to scene types and final depth is generated by cues which can effectively represent the current scene.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.435-449
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• 2023

The state-of-the-art video-based point cloud compression(V-PCC) has a high efficiency of compressing 3D point cloud by projecting points onto 2D images. These images are then padded and compressed by High-Efficiency Video Coding(HEVC). Pixels in padded 2D images are classified into three groups including origin pixels, padded pixels and unoccupied pixels. Origin pixels are generated from projection of 3D point cloud. Padded pixels and unoccupied pixels are generated by copying values from origin pixels during image padding. For padded pixels, they are reconstructed to 3D space during geometry reconstruction as well as origin pixels. For unoccupied pixels, they are not reconstructed. The rate distortion optimization(RDO) used in HEVC is mainly aimed at keeping the balance between video distortion and video bitrates. However, traditional RDO is unreliable for padded pixels and unoccupied pixels, which leads to significant waste of bits in geometry reconstruction. In this paper, we propose a new RDO scheme which takes 3D-Distortion into account instead of traditional video distortion for padded pixels and unoccupied pixels. Firstly, these pixels are classified based on the occupancy map. Secondly, different strategies are applied to these pixels to calculate their 3D-Distortions. Finally, the obtained 3D-Distortions replace the sum square error(SSE) during the full RDO process in intra prediction and inter prediction. The proposed method is applied to geometry frames. Experimental results show that the proposed algorithm achieves an average of 31.41% and 6.14% bitrate saving for D1 metric in Random Access setting and All Intra setting on geometry videos compared with V-PCC anchor.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.157-160
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• 2003

In this paper. we propose a simple and effective video scene change detection algorithm using a 3-D DCT. The 3-D DCT that we employ is a 2$\times$2$\times$2 DCT has simple computations composed only of adding and shifting operations. The simple average values of multiresolution represented video using the 2$\times$2$\times$2 DCT are used as a detection feature vector.