IMAGE MEDIA AND THE RESULTS OF LEARNING OUTCOMES OF KONTRASTIVE KULTURKUNDE COURSES OF THE STUDENTS OF GERMAN LANGUAGE EDUCATION STUDY PROGRAM, FKIP PATTIMURA UNIVERSITY, AMBON

The purpose of this study is to determine the influence of the use of image media on the learning outcomes of students of the German Language Education Study Program in Kontrastive Kulturkunde courses that use image media and those that do not use images. The use of image media applied in this study follows what Macaire and Hosch (2004: 67) have suggested about the function of images, that images can reactivate students' initial knowledge (Vorwissen der Schülerinnen und Schüler), show similarities/authenticity (Authentizität) and indicate actual situations (Aktualität), a communicative perspective image of an object and a representative image, which is a visual that depicts the state of nature and people's lives. (Perspektive und Repräsentativität) and which have similarities or differ with their own culture (Nähe oder Ferne zur eigenen Kultur). This research was motivated by the low learning outcomes of students in Kontrastive Kulturkunde courses. The type of this research used is experiment with one group pretest - posttest design with t-test analysis technique with significance level α = 0.05. Testing the effectiveness of this study is with the use of image media. The target of this study was 20 students of semester 4, German Language Education Study Program FKIP Pattimura University Ambon in Kontrastive Kulturkunde courses. The result of the calculation appears that, tcount > ttable=1,729 which is 11,103 > 1,729. Based on the results of the calculation it can be said that, there is a noticeable difference between the value after and before the application of the image media

GEOGRAPHICAL APPROACH TO STUDYING THE SYMBOLIC CAPITAL OF THE COUNTRY FROM THE POSITION OF THE POPULATION EXPECTED LIFE

The article reveals the theoretical and methodological issues of studying the symbolic capital of the territory. In the context of strengthening social priorities in the development of the global economy, it becomes necessary to apply new methods for assessing the attractiveness and competitiveness of countries around the world. The human development index has not lost the relevance of a formalized assessment of the quality of life of the population. It affects the formation of the country's image, but does not fully reflect the qualitative changes taking place in countries of different levels of development. The image and symbolic capital of the territory is investigated from the standpoint of social geography. Speaking about the formation of the image of a region (country) within the framework of social geography, we mean the process of strategic marketing of the territory, that is, not just the creation of a short-term set of associations, but a long-term instrument of territorial governance. Understanding the value and significance of the positive image of the territory should be a necessary element of geographical research. The perspective image of the country and the region is an integral attribute, the central link of the system of strategic planning and territorial marketing. The authors propose the use of the parameter of Life expectancy as an indicator of the standard of living and physical health of the population, which forms the symbolic capital of a territory (country). The analysis of the qualitative content of the indicator of life expectancy of the population is given. The emphasis is made on the need to use a typological approach that reveals the relationship between material and spiritual well-being and the life expectancy of the population. An original typology of the countries of the world is presented, proving the thesis that the success of the socio-economic development of the country can be judged by the duration of the expected and healthy life of the population.

Spherical panorama compositing through depth estimation

In this paper, we propose to work in the 2.5D space of the scene to facilitate composition of new spherical panoramas. For adding depths to spherical panoramas, we extend an existing method that was designed to estimate relative depths from a single perspective image through user interaction. We analyze the difficulties to interactively provide such depth information for spherical panoramas, through three different types of presentation. Then, we propose a set of basic tools to interactively manage the relative depths of the panoramas in order to obtain a composition in a very simple way. We conclude that the relative depths obtained by the extended depth estimation method are enough for the purpose of compositing new photorealistic panoramas through a few elementary editing tools.

Application of Plane Homography for Vehicle Speed Calculations in Traffic Accident Investigations

The analysis of vehicle speeds at the moment of traffic accidents is becoming increasingly important. To solve difficult calculations arising from video analysis when the shooting direction of the camera is the same as the driving direction of the vehicles, an improved plane homography method is proposed. This method is based on detecting the frame rate of and extracting all of the key image frames from a surveillance video. Next, a normalizing approach for the control points is proposed to reduce the ill-conditions of matrix calculations when the perspective image is rectified to an orthographic image. The information in the rectified image is then measured and recorded by extracting the mark point information. Finally, the corresponding curve of time and speed for the examined vehicle is created, which can be used to analyze the average braking deceleration of the accident-causing vehicle. This method can directly determine the speed of a vehicle using videos of a traffic accident without any reference to the dimensions of the vehicle itself. Considering an actual traffic accident as an example, the driving trajectories and velocity curves for two vehicles are obtained using this method. The proposed method can effectively overcome the shortcomings of the commonly used speed recognition methods and it is easy to utilize.

Monitoring Technique Using a Vision-based Single-Camera System for Reinforced Soil Retaining Wall

Reinforced soil retaining walls are widely applied, and their frequency of collapse increases along with their use. Safety inspections are regularly conducted to ensure the structural safety of such walls. However, unexpected collapses occur for different reasons, such as design and construction problems, maintenance issues, and natural disasters including intensive rainfall. In this study, a single-camera system is proposed to evaluate the behavior of a retaining wall based on a single-perspective image. Various feature matching methods were compared to determine the optimal method for monitoring the retaining wall structure. The behaviors of the retaining wall structure were analyzed using the optimal method. The results indicate that the KAZE method provides the best results for monitoring the behaviors of a retaining wall, with errors ranging from 0.03% to 7.37%. The proposed single-camera system is widely used to evaluate the stability of a structure with high accuracy.

Virtual and Augmented Reality Applications in Landscape Design and Project Presentation Techniques

After realizing that multi-storey buildings are contrary to human nature, the importance of natural landscape and green areas around it has been noticed. For this reason, people want to see how their environment will be in the design phase and the importance of project presentations is increasing day by day. Information technologies for spatial thinking, imagination and modelling have gradually started to be included in landscape design processes. The concept of virtual reality, augmented reality and immersive virtual reality are becoming more and more involved in our lives due to reasons such as the size of the devices getting smaller and their prices being relatively accessible to everyone. As an alternative to traditional presentation techniques and two-dimensional presentation techniques on the computer, making presentations in a virtual reality environment can be a stronger factor in people’s perception of the environment. In the study visual sets in basic, intermediate and advanced level of detail for the same landscape design and project site have been created. Each set consists of hand-drawn perspective image, computer aided perspective image, stereoscopic 360-degree VR image and an augmented reality model. In order to evaluate these visual sets, interviews were made with 10 landscape architects who are experts in the subject. As a result of the study, criteria’s for landscape presentations has been discussed and the advantages and disadvantages of landscape design presentations that will be created using virtual and augmented reality have been evaluated.

Lifelogging caption generation via fourth-person vision in a human–robot symbiotic environment

Automatic analysis of our daily lives and activities through a first-person lifelog camera provides us with opportunities to improve our life rhythms or to support our limited visual memories. Notably, to express the visual experiences, the task of generating captions from first-person lifelog images has been actively studied in recent years. First-person images involve scenes approximating what users actually see; therein, the visual cues are not enough to express the user’s context since the images are limited by his/her intention. Our challenge is to generate lifelog captions using a meta-perspective called “fourth-person vision”. The “fourth-person vision” is a novel concept which complementary exploits the visual information from the first-, second-, and third-person perspectives. First, we assume human–robot symbiotic scenarios that provide a second-person perspective from the camera mounted on the robot and a third-person perspective from the camera fixed in the symbiotic room. To validate our approach in this scenario, we collect perspective-aware lifelog videos and corresponding caption annotations. Subsequently, we propose a multi-perspective image captioning model composed of an image-wise salient region encoder, an attention module that adaptively fuses the salient regions, and a caption decoder that generates scene descriptions. We demonstrate that our proposed model based on the fourth-person concept can greatly improve the captioning performance against single- and double-perspective models.

Teleoperated Vehicle-Perspective Predictive Display Accounting for Network Time Delays

Variable network time-delays in data-transmission is the major problem in tele-operating a vehicle. Even on LTE network, variability of these delays is high (70–150 ms ping). This paper presents an innovative approach of providing the remote operator a forecasted video stream which replicates future perspective of vehicle’s FOV upon reception of maneuvering commands. First, vehicle position is predicted accounting for its speed and data transmission delays. Then perspective image transformation2 is performed to get exact new perspective of vehicle FOV corresponds to the predicted position. This approach addresses both issues, time-delays as well as its variability. Only one display, which shows frontward FOV is availed for mock-up.

One Shot Crowd Counting with Deep Scale Adaptive Neural Network

This paper aims to utilize the deep learning architecture to break through the limitations of camera perspective, image background, uneven crowd density distribution and pedestrian occlusion to estimate crowd density accurately. In this paper, we proposed a new neural network called Deep Scale-Adaptive Convolutional Neural Network (DSA-CNN), which can convert a single crowd image to density map for crowd counting directly. For a crowd image with any size and resolution, our algorithm can output the density map of the crowd image by end-to-end method and finally estimate the number of the crowd in the image. The proposed DSA-CNN consists of two parts: the seven layers CNN network structure and DSA modules. In order to ensure the proposed method is robust to camera perspective effect, DSA-CNN has adopted different sizes of filters in the network and combines them ingeniously. In order to reduce the depth of the data to increase the speed of training, the proposed method utilized 1 × 1 filter in DSA module. To validate the effectiveness of the proposed model, we conducted comparative experiments on four popular public datasets (ShanghiTech dataset, UCF_CC_50 dataset, WorldExpo’10 dataset and UCSD dataset). We compare the proposed method with other well-known algorithms on the MAE and MSE indicators, such as MCNN, Switching-CNN, CSRNet, CP-CNN and Cascaded-MTL. Experimental results show that the proposed method has excellent performance. In addition, we found that the proposed model is easily trained, which further increases the usability of the proposed model.