• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1851-1863
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• 2015

– In the paper, to handle the problem of traditional bag-of-features model ignoring the spatial relationship of local features in human action recognition, we proposed a Multiscale Spatial Position Coding under Locality Constraint method. Specifically, to describe this spatial relationship, we proposed a mixed feature combining motion feature and multi-spatial-scale configuration. To utilize temporal information between features, sub spatial-temporal-volumes are built. Next, the pooled features of sub-STVs are obtained via max-pooling method. In classification stage, the Locality-Constrained Group Sparse Representation is adopted to utilize the intrinsic group information of the sub-STV features. The experimental results on the KTH, Weizmann, and UCF sports datasets show that our action recognition system outperforms the classical local ST feature-based recognition systems published recently.

• ETRI Journal
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• v.33 no.4
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• pp.589-599
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• 2011

This paper presents an image description and matching scheme using synthetic features for a recommendation service. The recommendation service is an example of smart search because it offers something before a user's request. In the proposed extraction scheme, an image is described by synthesized spatial and statistical features. The spatial feature is designed to increase the discriminability by reflecting delicate variations. The statistical feature is designed to increase the robustness by absorbing small variations. For extracting spatial features, we partition the image into concentric circles and extract four characteristics using a spatial relation. To extract statistical features, we adapt three transforms into the image and compose a 3D histogram as the final statistical feature. The matching schemes are designed hierarchically using the proposed spatial and statistical features. The result shows that each feature is better than the compared algorithms that use spatial or statistical features. Additionally, if we adapt the proposed whole extraction and matching scheme, the overall performance will become 98.44% in terms of the correct search ratio.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.141-147
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• 2009

A analysis on the spatial features is required for exploratory spatial data analysis of information about space location(population ecological factor, social ecological factor) to manage the store factors, the service industry, etc. Therefore, the purpose of this study is to provide correlation analysis method between the types of service trade using dependence between spatial objects on the geographical space and statistical correlation and to analyze the spatial features through the deduction of correlation analysis between the types of the neighborhood trade area.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.128-132
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• 2002

One of the fundamental components important to the analysis of spatial objects is to represent topological relationships between spatial features. Users of geographic information systems retrieve a lot of objects from spatial database and analyze their condition by means of topological relationships. The existing methods that represent these relationships have the disadvantage that they have limited information in $R^2$. In this paper, we represent and define the topological relationships between 3-dimensional spatial objects using the several representing methods of 2-dimensional features. We use the diverse representing methods, which include the 4-, 9-intersection, dimension extended and calculus-based method. Furthermore, we discuss OGC's topological relationships and operators for 3-dimensional spatial data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.400-404
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• 1997

This paper presents spatial relationshaps and engineering features for the feature based modeling of Sheet Metal Weld Assemblies (SMWA) that are made of sheet metal components through are welding processes. Spatial relationships in ProMod-S, a sheet metal product modeler,are further extended for the SMWA modeling. Some spatial relationships for special weld joint types are newly introduced. The geometrical and topological relations between spatial reationship, mating features, and assembly features are defined. Finally, assembly data stucturess for the product modeling of SMWA are proposed. They are an engineering relation to represent the constraints between component features, and a mating bond to integrate component design information.

• International Journal of Human Ecology
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• v.14 no.1
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• pp.87-102
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• 2013

This study investigated residents' preferences for spatial features of sitting areas in assisted living facilities, and provides recommendations for planning sitting areas to support residents' spatial preferences and social interaction. The study participants were 69 residents of eight assisted living facilities (30+ resident capacity), located in south central Texas. A photographic comparison method was used, in which residents were shown 20 matched pairs of photos, with a single feature digitally modified in each pair, and asked to select which environmental representation they preferred. The hypothesized spatial characteristics were identified in practice based literature as those that may encourage usage of sitting areas: viewability, variety, homelikeness, and privacy. Most of the hypothesized features were preferred by participants, with the highest preference found for non-institutional furniture arrangements and naturalness, followed by increasing enclosure and variety of seating. Preference was less significant for domestic cues such as carpeted floors, divided light windows, and boundaries defined by different colored material or columns, possibly due to their physical impairments or preference for visual openness. Participants' level of mobility assistance was significantly related to their preference for some features, such as seating with people-watching capability, and carpeted floors. The findings have implications for facility architects and administrators engaged in resident-oriented spatial planning.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.4
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• pp.45-55
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• 2018

The purpose of this study is to analyze common features and methodological differences of PN-spatial characteristics found in architectural theories and works of contemporary young architects in Japan, such as Sou Fujimoto, Yo shimada, Keisuke Maeda and Junya Ishigami. These architects have paid attention to space between nature and inner space and have tried to establish their own architectural theory on that. Such space is ambiguous and PN-spatial in a way that it has features of both nature and inner space. Ambiguousness is a characteristic of modern architecture and PN-spatial characteristics are one of the features of Japanese architecture. This study aims to analyze the architectural theories and works of contemporary young architects in Japan from the perspective of PN-space and to draw methodological differences and common features. Their theories and works have common features in terms of 'ambiguous spatial boundary', 'unregulated spatial territory', 'detoured circulation' and 'architectural motifs', but each has their own methodology. To sum up, the works and theories of the Japanese young architects contain the philosophy and discourse of modern architecture in general. To be sure, they clearly have characteristics of Japanese architecture, which needs to be studied constantly.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.361-364
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• 2008

It is well known that combining spatial and spectral information can improve land use classification from satellite imagery. High spatial resolution classification has a limitation when only using the spectral information due to the complex spatial arrangement of features and spectral heterogeneity within each class. Therefore, extracting the spatial information is one of the most important steps in high resolution satellite image classification. In this paper, we propose a new spatial feature extraction method. The extracted features are integrated with spectral bands to improve overall classification accuracy. The classification is achieved by applying a Support Vector Machines classifier. In order to evaluate the proposed feature extraction method, we applied our approach to KOMPSAT-2 data and compared the result with the other methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1595-1613
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• 2017

The IR camera and laser-based IR projector provide an effective solution for real-time collection of moving targets in RGB-D videos. Different from the traditional RGB videos, the captured depth videos are not affected by the illumination variation. In this paper, we propose a novel feature extraction framework to describe human activities based on the above optical video capturing method, namely spatial-temporal texture features for 3D human activity recognition. Spatial-temporal texture feature with depth information is insensitive to illumination and occlusions, and efficient for fine-motion description. The framework of our proposed algorithm begins with video acquisition based on laser projection, video preprocessing with visual background extraction and obtains spatial-temporal key images. Then, the texture features encoded from key images are used to generate discriminative features for human activity information. The experimental results based on the different databases and practical scenarios demonstrate the effectiveness of our proposed algorithm for the large-scale data sets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2361-2376
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• 2023

The electrocardiogram (ECG) signal is commonly used to screen and diagnose cardiovascular diseases. In recent years, deep neural networks have been regarded as an effective way for automatic ECG disease diagnosis. The convolutional neural network is widely used for ECG signal extraction because it can obtain different levels of information. However, most previous studies adopt single scale convolution filters to extract ECG signal features, ignoring the complementarity between ECG signal features of different scales. In the paper, we propose a dual-scale network with convolution filters of different sizes for 12-lead ECG classification. Our model can extract and fuse ECG signal features of different scales. In addition, different spatial and time periods of the feature map obtained from the 12-lead ECG may have different contributions to ECG classification. Therefore, we add a spatial-temporal attention to each scale sub-network to emphasize the representative local spatial and temporal features. Our approach is evaluated on PTB-XL dataset and achieves 0.9307, 0.8152, and 89.11 on macro-averaged ROC-AUC score, a maximum F1 score, and mean accuracy, respectively. The experiment results have proven that our approach outperforms the baselines.