• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.11
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• pp.1091-1097
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• 2012

Nowadays, some movie theaters provide additional sensory information in 3D movies to enhance visually induced motion perception. However, no studies have investigated how motion perception increases. Thus, in this study, we examined the effect of visual coherent sensory information on visually induced motion perception and quantification of sensory information. A visual stimulus rotated sinusoidally and visual coherent sensory information were applied as vibrations to a subject's foot. We measured the sway of the subject's body by using a force plate and somatosensory bar rotation that represents the subject's perception of the horizon using an encoder. By using this data, we obtained the weight of the sensory information using a Kalman filter. As a result, it was found that subjects rotated the somatosensory bar more when visual coherent vibrations were applied. The weight of vision also increased when visual coherent vibrations were applied. Thus, we can conclude that visual coherent sensory information tends to enhance visually induced motion perception and weight of vision.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3806-3825
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• 2016

This paper brings out a neoteric frame of reference for visual semantic based 3d video search and retrieval applications. Newfangled 3D retrieval application spotlight on shape analysis like object matching, classification and retrieval not only sticking up entirely with video retrieval. In this ambit, we delve into 3D-CBVR (Content Based Video Retrieval) concept for the first time. For this purpose we intent to hitch on BOVW and Mapreduce in 3D framework. Here, we tried to coalesce shape, color and texture for feature extraction. For this purpose, we have used combination of geometric & topological features for shape and 3D co-occurrence matrix for color and texture. After thriving extraction of local descriptors, TB-PCT (Threshold Based- Predictive Clustering Tree) algorithm is used to generate visual codebook. Further, matching is performed using soft weighting scheme with L₂ distance function. As a final step, retrieved results are ranked according to the Index value and produce results .In order to handle prodigious amount of data and Efficacious retrieval, we have incorporated HDFS in our Intellection. Using 3D video dataset, we fiture the performance of our proposed system which can pan out that the proposed work gives meticulous result and also reduce the time intricacy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2068-2086
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• 2011

Based on the quincunx sub-sampling grid, the New Interleaved Hierarchical INTerpolation (NIHINT) method is recognized as a superior pyramid data structure for the lossless and progressive coding of natural images. In this paper, we propose a new image interpolation algorithm, Edge Adaptive Hierarchical INTerpolation (EAHINT), for a further reduction in the entropy of interpolation errors. We compute the local variance of the causal context to model the strength of a local edge around a target pixel and then apply three statistical decision rules to classify the local edge into a strong edge, a weak edge, or a medium edge. According to these local edge types, we apply an interpolation method to the target pixel using a one-directional interpolator for a strong edge, a multi-directional adaptive weighting interpolator for a medium edge, or a non-directional static weighting linear interpolator for a weak edge. Experimental results show that the proposed algorithm achieves a better compression bit rate than the NIHINT method for lossless image coding. It is shown that the compression bit rate is much better for images that are rich in directional edges and textures. Our algorithm also shows better rate-distortion performance and visual quality for progressive image transmission.

• Journal of the Korean Society for Railway
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• v.13 no.6
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• pp.552-558
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• 2010

Ride comfort of railway vehicles is affected by many factors, such as vibration, noise, smell, temperature, visual stimuli, humidity and a seat design. In general, vibration, which originates from vehicle motion, is considered as the primary concern. In evaluating the ride comfort, relationship between passenger's feeling and vibration characteristics is very important because human feeling is dependent on frequency spectrum of vibration. Therefore, the weighing functions in frequency domain are used to evaluate the ride comfort of railway vehicles. In the present paper, we have analyzed the characteristics of the frequency weighting curves defined in many standards and reviewed the effect resulting from their difference on the ride comfort.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.5
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• pp.822-832
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• 1994

DSC-HDTV image compression algorithm removes spatial, temporal, and amplitude redundancies of an image by using transform coding, motion-compensated predictive coding, and adaptive quantization, respectively. In this paper, leak processing method which is used to recover image quality quickly from scene change and transmission error and adaptive quantization using perceptual weighting factor obtained by HVS are proposed. Perceptual weighting factor is calculated by contrast sensitivity, spatio-temporal masking and frequency sensitivity. Adaptive quantization uses the perceptual weighting factor and global distortion level from buffer history state. Redundant bits according to adaptation of HVS are used for the next image coding. In the case of scene change, DFD using motion compensated predictive coding has high value, large bit rate and unstabilized buffer states since reconstructed image has large quantization noise. Thus, leak factor is set to 0 for scene change frame and leak factor to 15/16 for next frame, and global distortion level is calculated by using standard deviation. Experimental results show that image quality of the proposed method is recovered after several frames and then buffer status is stabilized.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.4
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• pp.344-365
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• 2009

The performance of a tracking system is greatly increased if multiple types of sensors are combined to achieve the objective of the tracking instead of relying on single type of sensor. To conduct the multi-modal tracking, we have previously developed a multi-modal sensor-based tracking model where acoustic sensors mainly track the objects and visual sensors compensate the tracking errors [1]. In this paper, we find a network synchronization problem appearing in the developed tracking system. The problem is caused by the different location and traffic characteristics of multi-modal sensors and non-synchronized arrival of the captured sensor data at a processing server. To effectively deliver the sensor data, we propose a time-based packet aggregation algorithm where the acoustic sensor data are aggregated based on the sampling time and sent to the server. The delivered acoustic sensor data is then compensated by visual images to correct the tracking errors and such a compensation process improves the tracking accuracy in ideal case. However, in real situations, the tracking improvement from visual compensation can be severely degraded due to the aforementioned network synchronization problem, the impact of which is analyzed by simulations in this paper. To resolve the network synchronization problem, we differentiate the service level of sensor traffic based on Weight Round Robin (WRR) scheduling at the routers. The weighting factor allocated to each queue is calculated by a proposed Delay-based Weight Allocation (DWA) algorithm. From the simulations, we show the traffic differentiation model can mitigate the non-synchronization of sensor data. Finally, we analyze expected traffic behaviors of the tracking system in terms of acoustic sampling interval and visual image size.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.4
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• pp.98-105
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• 1989

Various models incorporating Human Visual System (HVS) with the Hadamard transform (HT) represented by Walsh functions are considered. Using the exact frequency components of HT basis functions, the optimum modulation transfer function (MTF) which has a higher peak frequency than DCT schemes is obtimum modulation transfer function (MTF) which has a higher peak frequency than DCT schemes is obtained analytically and visually. The main criterion, for error measurement, is errors at the block boundaries which is an important factor in transform coding. The scheme which has no inverse HVS is proposed. It causes some degradation of image data but it is insignigicant. Crossing area of 4 blocks is equalized by the HVS weighting coefficients. The HVS weighted coding results in perceptually higher quality images compared with the unweighted scheme.

• Journal of Environmental Impact Assessment
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• v.2 no.1
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• pp.39-55
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• 1993

The importance of urban and regional natural park increases because of the needs for preserving the natural resources and providing with natural recreation space in nature. This planning of natural park management should be established based on the research of the various natural resources in the park. But for the lack of effective data synthesizing methods and concepts, only some restricted factors for zoning plan are considered even though GIS computer system for large complex simulation is used. Therefore, in this study three ecological zoning models such as Basic Factor Model (BFM), Visual Landscape Model (VLM) and Comprehensive Ecological Model (CEM) are proposed and applied to Byounsan Peninsula Nature Park(BPNP) for comparison with the current natural park zoning. The BFM has three components -elevation, slope and vegetation. The VLM has applied with six components -elevation, slope, vegetation, road type, and the visual distance. Finally the CEM's modelling factors have included all of BFM, VLM components are added with the land use type, nature and historic resource factors. The zoning concept of BPNP was based on "Minimization" focused on the specific factors. But introduced modelling concept is "Optimization" based on the total ecological environment. So the result of the modelling has larger area for preservation and development zoning compared with the current zoning whose characteristics are ambiguous which allows the environmental destruction. The future study issues will be the determination of the weighting factor, component reconsideration based on the ground truth data and the agriculture residential area zoning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3383-3397
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• 2023

Scene graphs serve as semantic abstractions of images and play a crucial role in enhancing visual comprehension and reasoning. However, the performance of Scene Graph Generation is often compromised when working with biased data in real-world situations. While many existing systems focus on a single stage of learning for both feature extraction and classification, some employ Class-Balancing strategies, such as Re-weighting, Data Resampling, and Transfer Learning from head to tail. In this paper, we propose a novel approach that decouples the feature extraction and classification phases of the scene graph generation process. For feature extraction, we leverage a transformer-based architecture and design an adaptive calibration function specifically for predicate classification. This function enables us to dynamically adjust the classification scores for each predicate category. Additionally, we introduce a Distribution Alignment technique that effectively balances the class distribution after the feature extraction phase reaches a stable state, thereby facilitating the retraining of the classification head. Importantly, our Distribution Alignment strategy is model-independent and does not require additional supervision, making it applicable to a wide range of SGG models. Using the scene graph diagnostic toolkit on Visual Genome and several popular models, we achieved significant improvements over the previous state-of-the-art methods with our model. Compared to the TDE model, our model improved mR@100 by 70.5% for PredCls, by 84.0% for SGCls, and by 97.6% for SGDet tasks.

• International Journal of Contents
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• v.11 no.1
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• pp.15-20
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• 2015

The purpose of this research is to study methods for performing transition that have visual representation of corresponding animations with no bounce in subsequently recognized user information when attempting to interact with a virtual 3D character in real-time using user motion. If the transitions of the animation are needed owing to a variety of external environments, continuous recognition of user information is required to correspond to the motion. The proposed method includes linear interpolation of the transition using cross-fades and blending techniques. The normalized playing time of the source animation was utilized for automatically calculating the transition interpolation length of the target animation and also as the criteria in selecting the crossfades and blending techniques. In particular, in the case of blending, the weighting value based on the degree of similarity between two animations is used as a blending parameter. Accordingly, transitions for visually excellent animation are performed on interactive holographic projection systems.