• Journal of IKEEE
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• v.20 no.1
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• pp.31-44
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• 2016

This paper presents a hole-filling algorithm based on extrapolating spatial-temporal background information used in view synthesis for free-viewpoint television. A new background codebook is constructed and updated in order to extract reliable temporal background information. In addition, an estimation of spatial local background values is conducted to discriminate an adaptive boundary between the background region and the foreground region as well as to update the information about the hole region. The holes then are filled by combining the spatial background information and the temporal background information. In addition, an exemplar-based inpainting technique is used to fill the rest of holes, in which a priority function using background-depth information is defined to determine the order in which the holes are filled. The experimental results demonstrated that the proposed algorithm outperformed the other comparative methods about average 0.3-0.6 dB, and that it synthesized satisfactory views regardless of video characteristics and type of hole region.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.67-80
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• 2017

This paper presents a hole-filling method using extrapolated spatio-temporal background information to obtain a synthesized view. A new temporal background model using non-overlapped patch based background codebook is introduced to extrapolate temporal background information In addition, a depth-map driven spatial local background estimation is addressed to define spatial background constraints that represent the lower and upper bounds of a background candidate. Background holes are filled by comparing the similarities between the temporal background information and the spatial background constraints. Additionally, a depth map-based ghost removal filter is described to solve the problem of the non-fit between a color image and the corresponding depth map of a virtual view after 3-D warping. Finally, an inpainting is applied to fill in the remaining holes with the priority function that includes a new depth term. The experimental results demonstrated that the proposed method led to results that promised subjective and objective improvement over the state-of-the-art methods.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.15-22
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• 2010

Background generation is very important for accurate object tracking in video surveillance systems. Traditional background generation techniques have some problems with non-moving objects for longer periods. To overcome this problem, we propose a newbackground generation method using mean-shift and Fast Marching Method (FMM) to use pixel information along temporal and spatial dimensions. The mode of pixel value density along time axis is estimated by mean-shift algorithm and spatial information is evaluated by FMM, and then they are used together to generate a desirable background in the existence of non-moving objects during longer period. Experimental results show that our proposed method is more efficient than the traditional method.

• 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.

• Journal of Broadcast Engineering
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• v.15 no.4
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• pp.474-486
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• 2010

In this paper, we propose a new method for detection moving object contour using spatial and temporal edge. In general, contour pixels of the moving object are likely present around pixels with high gradient value along the time axis and the spatial axis. Therefore, we can detect the contour of the moving objects by finding pixels which have high gradient value in the time axis and spatial axis. In this paper, we introduce a new computation method, termed as temporal edge, to compute an gradient value along the time axis for any pixel on an image. The temporal edge can be computed using two input gray images at time t and t-2 using the Sobel operator. Temporal edge is utilized to detect a candidate region of the moving object contour and then the detected candidate region is used to extract spatial edge information. The final contour of the moving object is detected using the combination of these two edge information, which are temporal edge and spatial edge, and then the post processing such as a morphological operation and a background edge removing procedure are applied to remove noise regions. The complexity of the proposed method is very low because it dose not use any background scene and high complex operation, therefore it can be applied to real-time applications. Experimental results show that the proposed method outperforms the conventional contour extraction methods in term of processing effort and a ghost effect which is occurred in the case of entropy method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.9-21
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• 2004

The current paper proposes a genetic algorithm (GA)-based segmentation method that can automatically extract and track moving objects. The proposed method mainly consists of spatial and temporal segmentation; the spatial segmentation divides each frame into regions with accurate boundaries, and the temporal segmentation divides each frame into background and foreground areas. The spatial segmentation is performed using chromosomes that evolve distributed genetic algorithms (DGAs). However, unlike standard DGAs, the chromosomes are initiated from the segmentation result of the previous frame, then only unstable chromosomes corresponding to actual moving object parts are evolved by mating operators. For the temporal segmentation, adaptive thresholding is performed based on the intensity difference between two consecutive frames. The spatial and temporal segmentation results are then combined for object extraction, and tracking is performed using the natural correspondence established by the proposed spatial segmentation method. The main advantages of the proposed method are twofold: First, proposed video segmentation method does not require any a priori information second, the proposed GA-based segmentation method enhances the search efficiency and incorporates a tracking algorithm within its own architecture. These advantages were confirmed by experiments where the proposed method was success fully applied to well-known and natural video sequences.

• International Journal of Contents
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• v.11 no.1
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• pp.21-30
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• 2015

A simulated realistic virtual environment is inhabited by autonomous cyber-humans who play the roles of agents in events. A key element, which enables this realism, is the historical context formed by time and space. A knowledge-representation scheme, composed of both spatial and temporal aspects needed by the agent to respond to dynamically changing situations, is essential for the design of a realistic virtual agent. In this work, spatial and temporal aspects of dynamic situations in the virtual environment have been formalized as a key component of our knowledge-representation scheme. This scheme provides a mathematical framework to construct realistic virtual situations that change with time, and background knowledge for agents in the simulated environment to deduce new pieces of information and plan against changing situations.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.746-755
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• 2013

This paper presents a three dimensional bilateral filter detecting target trajectory, extracting spatial target information using two dimensional bilateral filter and temporal target information using one dimensional bilateral filter. In order to discriminate edge pixel with flat background and target region spatially and temporally, spatial and temporal variance are used for an image and temporal profile. With this procedure, background and background profile are predicted without original target through two dimensional and one dimensional bilateral filter. Finally, using spatially predicted background and temporally predicted background profile, small target can be detected. For comparison of existing target detection methods and the proposed method, the receiver operating characteristics (ROC) is used in experimental results. Experimental results show that the proposed method has superior target detection rate and lower false alarm rate.

• The KIPS Transactions:PartB
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• v.17B no.6
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• pp.405-412
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• 2010

Previous background generation techniques showed bad performance in complex environments since they used only temporal contexts. To overcome this problem, in this paper, we propose a new background generation method which incorporates spatial as well as temporal contexts of the image. This enabled us to obtain 'clean' background image with no moving objects. In our proposed method, first we divided the sampled frame into m*n blocks in the video sequence and classified each block as either static or non-static. For blocks which are classified as non-static, we used MRF framework to model them in temporal and spatial contexts. MRF framework provides a convenient and consistent way of modeling context-dependent entities such as image pixels and correlated features. Experimental results show that our proposed method is more efficient than the traditional one.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.11
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• pp.5011-5017
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• 2016

Background: Cervical cancer is a major public health problem worldwide. There have been several studies indicating that risk is associated with geographic location and that the incidence of cervical cancer has changed over time. In Thailand, incidence rates have also been found to be different in each region. Methods: Participants were women living or having lived in upper Northern Thailand and subjected to cervical screening at Maharaj Nakorn Chiang Mai Hospital between January 2010 and December 2014. Generalized additive models with Loess smooth curve fitting were applied to estimate the risk of cervical cancer. For the spatial analysis, Google Maps were employed to find the geographical locations of the participants' addresses. The Quantum Geographic Information System was used to make a map of cervical cancer risk. Two univariate smooths: x equal to the residency duration was used in the temporal analysis of residency duration, and x equal to the calendar year that participants moved to upper Northern Thailand or birth year for participants already living there, were used in the temporal analysis of the earliest year. The spatial-temporal analysis was conducted in the same way as the spatial analysis except that the data were split into overlapping calendar years. Results: In the spatial analysis, the risk of cervical cancer was shown to be highest in the Eastern sector of upper Northern Thailand (p-value <0.001). In the temporal analysis of residency duration, the risk was shown to be steadily increasing (p-value =0.008), and in the temporal analysis of the earliest year, the risk was observed to be steadily decreasing (p-value=0.016). In the spatial-temporal analysis, the risk was stably higher in Chiang Rai and Nan provinces compared to Chiang Mai province. According to the display movement over time, the odds of developing cervical cancer declined in all provinces. Conclusions: The risk of cervical cancer has decreased over time but, in some areas, there is a higher risk than in the major province of Chiang Mai. Therefore, we should promote cervical cancer screening coverage in all areas, especially where access is difficult and/or to women of lower socioeconomic status.