• Title/Summary/Keyword: automatic composition

Search Result 165, Processing Time 0.026 seconds

Generating Extreme Close-up Shot Dataset Based On ROI Detection For Classifying Shots Using Artificial Neural Network (인공신경망을 이용한 샷 사이즈 분류를 위한 ROI 탐지 기반의 익스트림 클로즈업 샷 데이터 셋 생성)

  • Kang, Dongwann;Lim, Yang-mi
    • Journal of Broadcast Engineering
    • /
    • v.24 no.6
    • /
    • pp.983-991
    • /
    • 2019
  • This study aims to analyze movies which contain various stories according to the size of their shots. To achieve this, it is needed to classify dataset according to the shot size, such as extreme close-up shots, close-up shots, medium shots, full shots, and long shots. However, a typical video storytelling is mainly composed of close-up shots, medium shots, full shots, and long shots, it is not an easy task to construct an appropriate dataset for extreme close-up shots. To solve this, we propose an image cropping method based on the region of interest (ROI) detection. In this paper, we use the face detection and saliency detection to estimate the ROI. By cropping the ROI of close-up images, we generate extreme close-up images. The dataset which is enriched by proposed method is utilized to construct a model for classifying shots based on its size. The study can help to analyze the emotional changes of characters in video stories and to predict how the composition of the story changes over time. If AI is used more actively in the future in entertainment fields, it is expected to affect the automatic adjustment and creation of characters, dialogue, and image editing.

A Study on the Application of a Drone-Based 3D Model for Wind Environment Prediction

  • Jang, Yeong Jae;Jo, Hyeon Jeong;Oh, Jae Hong;Lee, Chang No
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.39 no.2
    • /
    • pp.93-101
    • /
    • 2021
  • Recently, with the urban redevelopment and the spread of the planned cities, there is increasing interest in the wind environment, which is related not only to design of buildings and landscaping but also to the comfortability of pedestrians. Numerical analysis for wind environment prediction is underway in many fields, such as dense areas of high-rise building or composition of the apartment complexes, a precisive 3D building model is essentially required in this process. Many studies conducted for wind environment analysis have typically used the method of creating a 3D model by utilizing the building layer included in the GIS (Geographic Information System) data. These data can easily and quickly observe the flow of atmosphere in a wide urban environment, but cannot be suitable for observing precisive flow of atmosphere, and in particular, the effect of a complicated structure of a single building on the flow of atmosphere cannot be calculated. Recently, drone photogrammetry has shown the advantage of being able to automatically perform building modeling based on a large number of images. In this study, we applied photogrammetry technology using a drone to evaluate the flow of atmosphere around two buildings located close to each other. Two 3D models were made into an automatic modeling technique and manual modeling technique. Auto-modeling technique is using an automatically generates a point cloud through photogrammetry and generating models through interpolation, and manual-modeling technique is a manually operated technique that individually generates 3D models based on point clouds. And then the flow of atmosphere for the two models was compared and analyzed. As a result, the wind environment of the two models showed a clear difference, and the model created by auto-modeling showed faster flow of atmosphere than the model created by manual modeling. Also in the case of the 3D mesh generated by auto-modeling showed the limitation of not proceeding an accurate analysis because the precise 3D shape was not reproduced in the closed area such as the porch of the building or the bridge between buildings.

A Study on the Behavior and Deposition of Acid Precipitation-comparison of Chemical Composition of Rain Water between Chunchon and seoul (산성강하물의 침착량과 동태 해명에 관한 연구-춘천과 서울 강우의 화학조성 비교)

  • Kim, Man-Goo;Kang, Mi-Hee;Lim, Yang-Suck;Park, Ki-Jun;Hwang, Hoon;Lee, Bo-Kyung;Hong, Seung-Hee;Lee, Dong-Soo
    • Journal of Korean Society for Atmospheric Environment
    • /
    • v.15 no.2
    • /
    • pp.89-100
    • /
    • 1999
  • The rain water samples were collected at Chunchon and Seoul by using wet only automatic sampler from January 1996 through 1997. The daily base rain water samples collected over than 95% rainy events components, $SO_4^{-2}$, $NO_3^-$, $CI^-$, NH_4^+$, $Ca^{2+}$, $Mg^{2+}$, $Na^+$, and $K^+$, by ion chromatography. In 1996, about 77% of sampled rain water showed below pH 5.6 and the 60% of rain water was lower than pH 5.0. The volume weighted average pH was 4.7 at all sites. In 1997, the volume weighted average pH was 4.6 and 4.9 at Seoul and Chunchon, respectively. Among the rain water samples,, 87% and 55% fo samples showed below than pH 5.6 and 5.0, respectively. The pH value of Chunchon was significantly (p<0.05) lower than Seoul at the rain samples for less than 20mm rainfall. However conductivity of the rain samples were 20.9$\mu$S/cm for 1996 and 27.7$\mu$S/cm for 1997 at Seoul, and 19.1$\mu$S/cm for 1996 and 14.1$\mu$S/cm for 1997 at Chunchon. $H_2SO_4$ and $HNO_3$ contributed 65.9% and 29.6% of free acidity at Seoul, respectively. The ratio of [$NO_3^-$]/[nss-$SO_4^{-2}$] were 0.43 at Seoul and 0.51 at Chunchon for rain samples for less than 20mm rainfall. The annual wet deposition of $CI^-$, $NO_3^-$, $SO_4^{-2}$, $H^+$M, $Na^+$, NH_4^+$, $K^+$, $Mg^{2+}$, and $Ca^{2+}$, respectively, 568.8kg/$ extrm{km}^2$, 1489.3kg/$\textrm{km}^2$, 3184.8kg/$\textrm{km}^2$, 20.9kg/$\textrm{km}^2$, 249.4kg/$\textrm{km}^2$, 1091.2kg/$\textrm{km}^2$, 189.8kg/ $\textrm{km}^2$, 90.2kg/$\textrm{km}^2$ and 702.4kg/$\textrm{km}^2$ at Seoul for 1996; 656.4kg/$\textrm{km}^2$, 2029.7kg/$\textrm{km}^2$, 3280.7kg/$\textrm{km}^2$, 27.2kg /$\textrm{km}^2$, 229.4kg/$\textrm{km}^2$, 1063.9kg/$\textrm{km}^2$, 106.9kg/$\textrm{km}^2$, 78.2kg/$\textrm{km}^2$, 645.3kg/$\textrm{km}^2$ at Seoul for 1997; 116.9kg/ $\textrm{km}^2$, 983.3kg/$\textrm{km}^2$, 1797.0kg/$\textrm{km}^2$, 21.4kg/$\textrm{km}^2$, 83.2kg/$\textrm{km}^2$, 648.1kg/$\textrm{km}^2$, 78.0kg/$\textrm{km}^2$, 22.2kg/$\textrm{km}^2$, 368.8kg/$\textrm{km}^2$ at chunchon for 1996; 100.2kg/$\textrm{km}^2$, 1077.6kg/$\textrm{km}^2$, 1754.0kg/$\textrm{km}^2$, 13.4kg/$\textrm{km}^2$, 146.0kg/$\textrm{km}^2$, 602.3kg/$\textrm{km}^2$, 88.8kg/$\textrm{km}^2$, 16.2kg/$\textrm{km}^2$ and 206.8kg/$\textrm{km}^2$ at chunchon for 1997.

  • PDF

Effects of Diet Food Containing Jerusalem Artichoke's Inulin, Lotus Leaf, and Herb on Weight and Body Fat of Obesity University Students (돼지감자의 이놀린, 연잎, 허브의 다이어트제제가 비만인의 체중 및 체성분에 미치는 영향)

  • Lee, Eun-Hye;Kang, Sang-Mo
    • Journal of Applied Biological Chemistry
    • /
    • v.52 no.1
    • /
    • pp.8-14
    • /
    • 2009
  • This study was conducted to assess the effects of diet food containing Jerusalem artichoke's inulin, lotus leaf, and herb on weight and body fat. Participants in this study were selected based on the following criteria: BMI over $25kg/m^2$, body fat percentage higher than 25%, abdominal obesity level of 0.85 measured by body composition measurement unit (ZEUS 9.9 PLUS, Korea) total 24 female and male university students over 20 of age were assigned to two different groups: control group and diet group and the study was carried out for 30 days. When we measured what the tester's body weight and height, we used an automatic measure machin which is called IMI-1000 from Immanuel company and when we measured what the hip and wist circumference, we used a tape measure. When we measured body mss index (BMI), body Int, body mass, lean mass, waist/hip ratio (WHB), obesity index, we used a ZEUS9.9 PLUS-Korea which is based on bioelectrical impedance analysis, The food intake was checked by means of diet record method to be input into CAN program in order to analyze nutrient intake. Our findings indicated that the diet group, as compared to the control group, lost weight of approximately 2.5 kg and showed statistically significant difference. In addition the level of body Int, muscle, abdominal obesity, obesity, waist and bottom measurement all showed significant decrease after study period. However, there was no big difference in body fat percentage because both body fat level and muscle level dropped together, Putting all these together, diet food in this study containing Jerusalem artichoke's inulin, lotus leaf powder, and herbs powder including nettle, eucalyptus was found to be effective in significant reduction of weight and body fat and obesity-related body indicators. Also, it is considered that this diet food has potential to prevent and improve effectively obesity from abnormal fat accumulation.

Snow Influence on the Chemical Characteristics of Winter Precipitation (강설이 겨울철 강수의 화학적 특성에 미치는 영향)

  • Kang, Gong-Unn;Kim, Nam-Song;Oh, Gyung-Jae;Shin, Dae-Yewn;Yu, Du-Cheol;Kim, Sang-Baek
    • Journal of Korean Society of Environmental Engineers
    • /
    • v.29 no.1
    • /
    • pp.113-125
    • /
    • 2007
  • To know the differences in ionic compositions in rain and snow as well as snow influence on the chemical characteristics of winter precipitation, precipitation samples were collected by the wet-only automatic precipitation sample, in winter(November-February) in the Iksan located in the northwest of Chonbuk from 1995 to 2000. The samples were analyzed for concentrations of water-soluble ion species, in addition to pH and electrical conductivity. The mean pH of winter precipitation was 4.72. According to the type of winter precipitation, the mean pH of rain was 4.67 and lower than 5.05 in snow. The frequencies of pH below 5.0 in rain were about 73%, while those in snow were about 30%. Snow contained 3 times higher concentrations of sea salt ion components originated from seawater than did rain in winter, mainly $Cl^-,\;Na^+$, and $Mg^{2+}$. Neglecting sea salt ion components, $nss-SO_4^{2-}$ and $NO_3^-$ were important anions and $NH_4^+$ and $nss-Ca^{2+}$ were important cations in both of rain and snow. Concentrations of $nss-SO_4^{2-}$ was 1.3 times higher in rain than in snow, while those of $nss-Ca^{2+}$ and $NO_3^-$ were 1.5 and 1.3 times higher in snow, respectively. The mean equivalent concentration ratio of $nss-SO_4^{2-}/NO_3^-$ in winter precipitation were 2.4, which implied that the relative contribution of sulfuric and nitric acids to the precipitation acidity was 71% and 29%, respectively. The ratio in rain was 2.7 and higher than 1.5 in snow. These results suggest that the difference of $NO_3^-$ in rain and snow could be due to the more effective scavenging of $HNO_3$ vapor than particulate sulfate or nitrate by snow. The lower ratio in snow than rain is consistent with the measurement results of foreign other investigators and with scavenging theory of atmospheric aerosols. Although substantial $nss-SO_4^{2-}$ and $NO_3^-$ were observed in both of rain and snow, the corresponding presence of $NH_4^+,\;nss-Ca^{2+},\;nss-K^+$ suggested the significant neutralization of rain and snow. Differences in chemical composition of non-sea salt ions and neutralizing rapacity of $NH_4^+,\;nss-Ca^{2+}$, and $nss-K^+$ between rain and snow could explain the acidity difference of rain and snow. Snow affected that winter precipitation could be less acidic due to its higher neutralizing rapacity.