Scene Transition Research Articles

SceneFusion: Room-Scale Environmental Fusion for Efficient Traveling Between Separate Virtual Environments.

Traveling between scenes has become a major requirement for navigation in numerous virtual reality (VR) social platforms and game applications, allowing users to efficiently explore multiple virtual environments (VEs). To facilitate scene transition, prevalent techniques such as instant teleportation and virtual portals have been extensively adopted. However, these techniques exhibit limitations when there is a need for frequent travel between separate VEs, particularly within indoor environments, resulting in low efficiency. In this article, we first analyze the design rationale for a novel navigation method supporting efficient travel between virtual indoor scenes. Based on the analysis, we introduce the SceneFusion technique that fuses separate virtual rooms into an integrated environment. SceneFusion enables users to perceive rich visual information from both rooms simultaneously, achieving high visual continuity and spatial awareness. While existing teleportation techniques passively transport users, SceneFusion allows users to actively access the fused environment using short-range locomotion techniques. User experiments confirmed that SceneFusion outperforms instant teleportation and virtual portal techniques in terms of efficiency, workload, and preference for both single-user exploration and multi-user collaboration tasks in separate VEs. Thus, SceneFusion presents an effective solution for seamless traveling between virtual indoor scenes.

Tentacle Microelectrode Arrays Uncover Soft Boundary Neurons in Hippocampal CA1.

Hippocampal CA1 neurons show intense firing at specific spatial locations, modulated by isolated landmarks. However, the impact of real-world scene transitions on neuronal activity remains unclear. Moreover, long-term neural recording during movement challenges device stability. Conventional rigid-based electrodes cause inflammatory responses, restricting recording durations. Inspired by the jellyfish tentacles, the multi-conductive layer ultra-flexible microelectrode arrays (MEAs) are developed. The tentacle MEAs ensure stable recordings during movement, thereby enabling the discovery of soft boundary neurons. The soft boundary neurons demonstrate high-frequency firing that aligns with the boundaries of scene transitions. Furthermore, the localization ability of soft boundary neurons improves with more scene transition boundaries, and their activity decreases when these boundaries are removed. The innovation of ultra-flexible, high-biocompatible tentacle MEAs improves the understanding of neural encoding in spatial cognition. They offer the potential for long-term in vivo recording of neural information, facilitating breakthroughs in the understanding and application of brain spatial navigation mehanisms.

Dynamic Object Recognition in Video Streams

Dynamic Object Recognition in Video Streams, essen- tial for advancements in video surveillance, autonomous systems, and robotics. Focusing on challenging scenarios like crowded- ness and rapid scene changes, the study introduces novel ob- ject detection and tracking techniques. Object segmentation in crowded scenes and trajectory analysis for simultaneous tracking in dense environments are explored, considering both immediate interactions and long-term movements. Adaptive object recognition algorithms, integrating event detection for rapid scene transitions, are investigated for their responsiveness. Additionally, the study incorporates advanced deep learning frameworks like Temporal Convolutional Networks (TCNs) and one-shot learning methods, enhancing the system’s adaptability to dynamic environments. Real- time processing efficiency is addressed through hardware accelera- tion and online learning strategies, contributing to the development of more efficient and adaptive dynamic object recognition systems for crowded and dynamic scenes. Index Terms—Computer Vision, Object recognition, Video, TCN, Robotics

The presentation of self via everyday vlogging: Analyzing everyday vlogs of Korean expatriates

Drawing on research about constructing identities through self-presentation (De Fina & Georgakopoulou, 2012) and Bamberg’s (2011a, b) sameness and difference, I demonstrate how Korean expatriates employ vlogging strategies to construct and present everyday self, especially vis-à-vis viewers. To do so, I analyze 27 daily vlogs of Korean expatriates living in Hong Kong, New York, and Tokyo. The vloggers present the mundanity of everyday life, using chronological organization, quick scene transitions, micro-details, and “historical present” (Wolfson, 1979). These vlogging strategies, I argue, create alignment with viewers, signaling that “my daily life is just like yours.” Simultaneously, the vloggers make everyday vlogs engaging and entertaining through offering explanatory notes and not providing translation of what is being spoken, especially when they present foreign city lives, cultures, and languages they experience by virtue of living abroad, to signal “my daily life is different from yours.” Everyday vlogging of Korean expatriates, as a type of “lifestreaming” (Marwick 2013), involves meaning making and identity construction processes through which Korean expatriates skillfully exert and express agency in (ab)normalizing their expatriate self and life, in connection to others, and thus achieve self-legitimacy and -empowerment.

Analyzing the Impact of Scene Transitions on Indoor Camera Localization through Scene Change Detection in Real-Time

Analyzing the Impact of Scene Transitions on Indoor Camera Localization through Scene Change Detection in Real-Time

DisCoVQA: Temporal Distortion-Content Transformers for Video Quality Assessment

Compared with spatial counterparts, temporal relationships between frames and their influences on video quality assessment (VQA) are still relatively under-studied in existing works. These relationships lead to two important types of effects for video quality. Firstly, some meaningless temporal variations (such as shaking, flicker, and unsmooth scene transitions) cause temporal distortions that degrade quality of videos. Secondly, the human visual system often has different attention to frames with different contents, resulting in their different importance to the overall video quality. Based on prominent time-series modeling ability of transformers, we propose a novel and effective transformer-based VQA method to tackle these two issues. To better differentiate temporal variations and thus capture the temporal distortions, we design the Spatial-Temporal Distortion Extraction (STDE) module that extracts multi-level spatial-temporal features with a video swin transformer tiny (Swin-T) backbone and uses temporal difference layer to further capture these distortions. To tackle with temporal quality attention, we propose the encoder-decoder-like temporal content transformer (TCT). We also introduce the temporal sampling on features to reduce the input length for the TCT, so as to improve the learning effectiveness and efficiency of this module. Consisting of the STDE and the TCT, the proposed Temporal Distortion-Content Transformers for Video Quality Assessment ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DisCoVQA</i> ) reaches state-of-the-art performance on several VQA benchmarks without any extra pre-training datasets and up to 10% better generalization ability than existing methods. We also conduct extensive ablation experiments to prove the effectiveness of each part in our proposed model, and provide visualizations to prove that the proposed modules achieve our intention on modeling these temporal issues. Our code is published at https://github.com/QualityAssessment/DisCoVQA.

A Novel Exploratory Graph-Based Analytical Tool for Functional Near-Infrared Spectroscopy in Naturalistic Experiments: An Illustrative Application in Typically Developing Children.

Naturalistic paradigms are being increasingly applied to investigate human brain function. Compared with resting-state and task-based paradigms in neuroimaging, naturalistic stimuli and situations can be potentially more readily translated to daily-life applications. Among neuroimaging modalities, functional near-infrared spectroscopy (fNIRS) is particularly suitable for naturalistic investigations and applications. However, specific and tailored statistical analysis to interrogate brain function using naturalistic fNIRS is warranted. Here, we describe an exploratory graph-centrality-based approach to investigating participants' spatiotemporal similarities from the fNIRS signal. We illustrate the usefulness of our approach in a sample of typically developing children (10 males and 9 females; mean age of 5.2 years old; sd = 0.78) while they watch the Inscapes movie designed for neuroimaging acquisition. A node in the left dorsal prefrontal cortex presented similar responses across children, and those fNIRS responses were in line with scene transitions in the movie stimulus. Our results suggest the feasibility of applying centrality graph-based measures to investigate brain function in naturalistic fNIRS during development.

게임 몰입 이론을 기반으로 한 RPG 게임 로딩 인터페이스 디자인 연구

The loading interface of game scene is an essential part of the game. From the perspective of the development of the game loading interface and the player's experience of the game based on the Game Flow model, Ratchet &amp; Clank: Rift Apart was taken as a research sample, the loading interface of scene conversion was taken as the object, the type of scene transition loading interface and the mode characteristics of different game loading interfaces were analyzed, the type and principle model of the scene transition loading interface was further analyzed in the study.

Cueing in Theatre: Timing and Temporal Variance in Rehearsals of Scene Transitions

This video-ethnographic study explores how professional actors and a director at the end of a theatrical rehearsal process coordinate transitions between rehearsed scenes. This is done through the development and use of cues, that is, ‘signals for action’. The aim is to understand how cues are developed and how timing in transitions is achieved by using the designed cues. Work on three different scene transitions is analysed using multimodal Conversation Analysis. The results show that cueing is a central tool for developing well-timed transitions, and how cues serve different purposes in the developing performance. There is no prior plan for how to achieve timely transitions. In all the analysed examples, it is an actor who must produce or act on the given cue who insists on its precise definition, followed by a negotiation on candidate cues, confirmation and specifying the cue. It is also actors who are primarily responsible for the timing of transitions, and the timing is solved through an interplay of clear-cut and embodied actions that allow for temporal variance. Cues are reflexively linked to actors’ observation and interpretation of other actors’ actions, which prevents a mechanical determination of timing in scene transition.

A virtual reality investigation of factors influencing landscape preferences: Natural elements, emotions, and media creation

Understanding natural landscape preferences is essential to creating attractive green spaces that promote the benefits people may receive from nature. Previous research on landscape preference has primarily relied on quantitative, theory-driven approaches that may neglect complex and detailed human feelings and thoughts, as well as still images, which may not represent moving immersive stimuli representative of real-world experiences. The current study sought to reveal the key reasons for landscape preferences using virtual reality (VR) and open-ended questions. Ninety-five university students in the U.S. watched six 360° videos of natural environments from Costa Rica and the U.S. We found that tropical beaches and rainforests were the favorite and the least favored landscapes in our sample, respectively. Preference rankings were explained by natural elements, emotional responses, and to a lesser degree, the creation of the 360° videos. Sounds, water, coastal elements, and feeling relaxed were the most frequent reasons for “favoriting” a video; greenery and feeling bored were the most frequent reasons for “least favoring” a video. Low arousal emotions (i.e., relaxing, boring) and multiple scene transitions played important roles in explaining preferences. The results demonstrated the relevance of landscape preference theories while suggesting a greater emphasis on open views, sounds, and rhythmic features of the coast for landscape planning and design.

A Visible Video Data Hiding Scheme Based on Fade-In and Fade-Out Effects Utilizing Barcodes

Data hiding techniques are usually applied into digital watermarking or digital fingerprinting, which is used to protect intellectual property rights or to avoid illegal copies of the original works. It has been pointed out that data hiding can be utilized as a communication medium. In conventional digital watermarking frameworks, it is required that the difference between the cover objects and the stego objects are quite small, such that the difference cannot be recognized by human sensory systems. On the other hand, the authors have proposed a ‘hearable’ data hiding technique for audio signals that can carry secret messages and can be naturally recognized as a musical piece by human ears. In this study, we extend the idea of the hearable data hiding into video signals by utilizing the visual effects. As visual effects, we employ fade-in and fade-out effects which can be used as a kind of visual rendering for scene transitions. In the proposed schemes, secret messages are generated as one-dimensional barcodes which are used for fade-in or fade-out effects. The present paper shows that the proposed schemes have the high accuracy in extracting the embedded messages even from the video signals captured by smartphones or tablets. It is also shown that the video signals conveying the embedded messages can be naturally recognized by human visual systems through subjective evaluation experiments.

AI-Based Video Clipping of Soccer Events

The current gold standard for extracting highlight clips from soccer games is the use of manual annotations and clippings, where human operators define the start and end of an event and trim away the unwanted scenes. This is a tedious, time-consuming, and expensive task, to the extent of being rendered infeasible for use in lower league games. In this paper, we aim to automate the process of highlight generation using logo transition detection, scene boundary detection, and optional scene removal. We experiment with various approaches, using different neural network architectures on different datasets, and present two models that automatically find the appropriate time interval for extracting goal events. These models are evaluated both quantitatively and qualitatively, and the results show that we can detect logo and scene transitions with high accuracy and generate highlight clips that are highly acceptable for viewers. We conclude that there is considerable potential in automating the overall soccer video clipping process.

MTG: Context-Based Music Composition for Tabletop Role-Playing Games

This project aims to compose background music in real-time for tabletop role-playing games. To accomplish this goal, we propose a system called MTG that listens to players' speeches in order to recognize the context of the current scene and generate background music to match the scene. A speech recognition system is used to transcribe players' speeches to text and a supervised learning algorithm detects when scene transitions take place. In its current version, a scene transition occurs whenever the emotional state of the narrative changes. Moreover, the background music is not generated, but selected based on its emotion from a library of hand-authored pieces. As future work, we plan to generate the background music considering the current scene context and the probability of scene transition. We also consider to retrieve more information from the narrative to detect scene transitions, such as the scene's location and time of the day as well as actions taken by characters.

Energy-Efficient Swarming Flight Formation Transitions Using the Improved Fair Hungarian Algorithm.

Recently, drone shows have impressed many people through a convergence of technology and art. However, these demonstrations have limited operating hours based on the battery life. Thus, it is important to minimize the unnecessary transition time between scenes without collision to increase operating time. This paper proposes a fast and energy-efficient scene transition algorithm that minimizes the transition times between scenes. This algorithm reduces the maximum drone movement distance to increase the operating time and exploits a multilayer method to avoid collisions between drones. In addition, a swarming flight system including robust communication and position estimation is presented as a concrete experimental system. The proposed algorithm was verified using the swarming flight system at a drone show performed with 100 drones.

풀 와이드 배너의 장면전환 움직임에 따른 감성분석

바쁜 현대인들의 필수 유통채널로 자리 잡고 있는 온라인 쇼핑몰은 주 광고매체인 배너광고의 역할이 매우 중요하다. 이미 오랜 시간 사용되어진 배너광고는 소비자들의 광고회피현상을 나타내기도 하는데, 이에 소비자들의 만족가치를 높이기 위해서는 새로운 표현요소를 필요로 한다. 따라서, 본 연구는 배너광고의 장면전환 움직임에 차이를 두고 소비자들의 감성변화를 알아보고자 한다. 움직임에 따른 감성선호도 변화를 알아보기 위해 의미분별법(Semantic Differential)이론을 통해 분석하였다. 연구를 위해 총 15쌍의 대표 감성어휘를 선정하고, 풀 와이드 배너에 카메라기법을 적용한 장면전환 16개를 제작한 후, 총 72명을 대상으로 실험을 실시하였다. 그 후 실험결과를 바탕으로 통계프로그램(SPSS)에 의한 주성분 분석을 실시해 최종결과를 도출하였다. 주성분분석 결과에 따라서 역동성, 무게감, 심미성에 해당하는 장면전환 움직임이 어디에 위치하는 지 알 수 있었고, 카메라기법에 따른 배너광고의 장면전환 움직임이 감상자의 감성 차이를 나타낸다는 것을 알 수 있었다. 또한, 기존 배너광고의 장면전환이 소비자들의 흥미를 감소시키고 있음을 유추할 수 있었다. 또한, 쇼핑몰이 추구하는 감성마케팅에 따라 다양한 장면전환을 적용할 수 있고, 보다 적극적인 표현요소로 광고효과를 가져 올 수 있음을 알 수 있었다. 본 연구에서 진행된 카메라기법 장면전환 외에도 새로운 동적 장면전환 연구가 활성화되어 보다 다양하고 수준 높은 장면전환 연구로 발전될 수 있기를 바란다.

A HUMAN–ENVIRONMENT TIMELINE

abstract Concern about accelerating human impact on Earth systems coincides with discussion of adding a new proposed geologic epoch that would document the Age of Humans. This research contributes a human-environment timeline prototype. Time-period classification provides academics and citizens alike with a common temporal reference frame for discussion and further investigation. A hierarchical human-environment timeline was built from analysis of entries in four geographic encyclopedias. Through grounded theory, an open-ended, qualitative analysis of dates identified important events in the human-environment relationship and major ideas that shaped environmental perception. The resulting timeline prototype features a typology of periods based on five relative timescales: lengthy Durations, Duration Revolutions, intermediate-scale Scenes, Scene Transitions, and shorter Intervals. Four long-term Durations emerge: Survival (2,598,050 to 318,050 BCE), Adaptation (318,050 to 4,050 BCE), Keystone (4,050 BCE to 1945 CE), and Acceleration (1945 CE –). The timeline provides a foundation for further scholarly analysis and thinking.

Rhythmic Tendencies in the Choreographies of Dairakudakan's Muramatsu Takuya

This article examines rhythm in the choreographies of Dairakudakan's Muramatsu Takuya using concepts from Henri Lefebvre's rhythmanalysis as a framework. Works analyzed include Dobu (Ditch, 2007), Sonna Tokikoso Warattero (To Laugh at Such a Time, 2008), Ana (Hole, 2009), and Wasureru, Omoidase (Forget, Remember, 2013). The article discusses how rhythm informs overriding themes, performer training, scenographic design, scene transitions, and contrasts between solo and group performance in each piece. Key concepts from Lefebvre's theory used to interpret Muramatsu's work include polyrhythmia, eurhythmia/arrhythmia, dressage, and secret rhythms. In comparing multiple performances, rhythmic similarities emerge in Muramatsu's oeuvre, such as a common rhythmic arc shaping each piece and similar choreographic strategies employed in order to maximize dramatic effects for an audience, often defined through their use of contrast.

Detection method of sports scene conversion for MPEG compressed video based on fuzzy logic

At present, the majority of sports games video adopts MPEG image technology, and MPEG video compression is the current more mainstream approach. After compression, the quality of the video will decline, and other practical problems. However, the existing detection methods of sports video scene conversion, when dealing with MPEG compressed video, are not ideal, often appear the phenomenon of missing detection and wrong detection. In order to solve this problem, this paper proposes a detection method of sports scene conversion on MPEG compressed video based on fuzzy logic. Introducing fuzzy logic into the detection method of video scene conversion is the highlight of this method. Firstly, this paper preprocessed the video image according to the Convention. In this paper, the recognition of image features and specific extraction methods are introduced in detail, and the extraction algorithm of image color features is further optimized. For the design of the detection method, the main innovation is to fully combine the fuzzy logic and macroblock information. In the existing detection methods, different detection schemes are given for the abrupt change of video scene and the gradual change of scene. Finally, in order to verify the actual effect of the detection method in this paper, an experimental analysis based on the keyframe complexity detection method is established. After a number of experiments including the experimental results of scene transition, analysis, and processing time, through the analysis of data, a step-by-step proof of this method has good accuracy and recall.

Establishing Shot Type Affects Arousal and Cognitive Load During Transitions Between Novel Interior Locations in Films.

An “establishing shot” prefaces a scene in a movie with a wide shot of the scene’s location. It is meant to help viewers process a shift to a new location. Establishing shots can depict the actors in the space in which they will be acting, the exterior of a building, or the larger geographic context of the scene. While use of an establishing shot is standard filmmaking practice, some argue that establishing shots are unnecessary. This study sought to investigate how effective four types of establishing shots are at helping viewers process location shifts. Pupil diameter was recorded using a MangoldVision eye tracking system as a measure of arousal and cognitive load. Oxygenation levels in the prefrontal cortex provided an additional measure of cognitive load assessed through functional near infrared spectroscopy (fNIRS). We expected scene transitions to be followed by transient increases in pupil diameter and oxygenation levels, suggesting increased cognitive load and arousal. We predicted that participants should experience less cognitive load and arousal after a transition to a new scene when that scene has been prefaced with an establishing shot and that these effects would be greatest for establishing shots that depict actors. We found that geographic establishing shots produced significantly lower average pupil diameter than all other establishing shot types and the use of no establishing shot. Actors establishing shots elicited significantly lower average pupil diameter values than the use of no establishing shot. Maximum and average oxygenation values for the actors establishing shot condition were significantly higher than for the exterior establishing shot condition. An alpha level of 0.05 was used for all analyses. These results suggest differences between pupil diameter and fNIRS in terms of the psychological phenomenon they measure, and may inform the design of future films.

Scene Transition and Scenario Change by Some Triggers for Improving Robotic Intelligence

Scene Transition and Scenario Change by Some Triggers for Improving Robotic Intelligence