Heterogeneous Trajectory Forecasting via Risk and Scene Graph Learning

Heterogeneous trajectory forecasting is critical for intelligent transportation systems, while it is challenging because of the difficulty for modeling the complex interaction relations among the heterogeneous road agents as well as their agent-environment constraint. In this work, we propose a risk and scene graph learning method for trajectory forecasting of heterogeneous road agents, which consists of a Heterogeneous Risk Graph (HRG) and a Hierarchical Scene Graph (HSG) from the aspects of agent category and their movable semantic regions. HRG groups each kind of road agents and calculates their interaction adjacency matrix based on an effective collision risk metric. HSG of driving scene is modeled by inferring the relationship between road agents and road semantic layout aligned by the road scene grammar. Based on this formulation, we can obtain an effective trajectory forecasting in driving situations, and superior performance to other state-of-the-art approaches is demonstrated by exhaustive experiments on the nuScenes, ApolloScape, and Argoverse datasets.Comment: Submitted to IEEE Transactions on Intelligent Transportation Systems, 202

Learning to Generate Unambiguous Spatial Referring Expressions for Real-World Environments

Referring to objects in a natural and unambiguous manner is crucial for effective human-robot interaction. Previous research on learning-based referring expressions has focused primarily on comprehension tasks, while generating referring expressions is still mostly limited to rule-based methods. In this work, we propose a two-stage approach that relies on deep learning for estimating spatial relations to describe an object naturally and unambiguously with a referring expression. We compare our method to the state of the art algorithm in ambiguous environments (e.g., environments that include very similar objects with similar relationships). We show that our method generates referring expressions that people find to be more accurate ($\sim$30% better) and would prefer to use ($\sim$32% more often).Comment: International Conference on Intelligent Robots and Systems (IROS 2019), Demo 1: Finding the described object (https://youtu.be/BE6-F6chW0w), Demo 2: Referring to the pointed object (https://youtu.be/nmmv6JUpy8M), Supplementary Video (https://youtu.be/sFjBa_MHS98

Crossroads: Interactive Music Systems Transforming Performance, Production and Listening

date-added: 2017-12-22 18:26:58 +0000 date-modified: 2017-12-22 18:38:33 +0000 keywords: mood-based interaction, intelligent music production, HCI local-url: https://qmro.qmul.ac.uk/xmlui/handle/123456789/12502 publisher-url: http://mcl.open.ac.uk/music-chi/uploads/19/HCIMUSIC_2016_paper_15.pdf bdsk-url-1: https://qmro.qmul.ac.uk/xmlui/bitstream/handle/123456789/12502/Barthet%20Crossroads%3A%20Interactive%20Music%20Systems%202016%20Accepted.pdfdate-added: 2017-12-22 18:26:58 +0000 date-modified: 2017-12-22 18:38:33 +0000 keywords: mood-based interaction, intelligent music production, HCI local-url: https://qmro.qmul.ac.uk/xmlui/handle/123456789/12502 publisher-url: http://mcl.open.ac.uk/music-chi/uploads/19/HCIMUSIC_2016_paper_15.pdf bdsk-url-1: https://qmro.qmul.ac.uk/xmlui/bitstream/handle/123456789/12502/Barthet%20Crossroads%3A%20Interactive%20Music%20Systems%202016%20Accepted.pdfdate-added: 2017-12-22 18:26:58 +0000 date-modified: 2017-12-22 18:38:33 +0000 keywords: mood-based interaction, intelligent music production, HCI local-url: https://qmro.qmul.ac.uk/xmlui/handle/123456789/12502 publisher-url: http://mcl.open.ac.uk/music-chi/uploads/19/HCIMUSIC_2016_paper_15.pdf bdsk-url-1: https://qmro.qmul.ac.uk/xmlui/bitstream/handle/123456789/12502/Barthet%20Crossroads%3A%20Interactive%20Music%20Systems%202016%20Accepted.pdfWe discuss several state-of-the-art systems that propose new paradigms and user workflows for music composition, production, performance, and listening. We focus on a selection of systems that exploit recent advances in semantic and affective computing, music information retrieval (MIR) and semantic web, as well as insights from fields such as mobile computing and information visualisation. These systems offer the potential to provide transformative experiences for users, which is manifested in creativity, engagement, efficiency, discovery and affect

A generic architecture for hybrid intelligent systems

The integration of different learning and adaptation techniques in one architecture, to overcome individual limitations and achieve synergetic effects through hybridization or fusion of these techniques, has in recent years contributed to a large number of new intelligent system designs. Most of these approaches, however, follow an ad hoc design methodology, further justified by success in certain application domains. Due to the lack of a common framework it remains often difficult to compare the various systems conceptually and evaluate their performance comparatively. In this paper we first aim at classifying state-of-the-art intelligent systems, which have evolved over the past decade in the soft computing community. We identify four categories, based on the systems, overall architecture: (1) single component systems, (2) fusion-based systems, (3) hierarchical systems, and (4) hybrid systems. We then introduce a unifying paradigm, derived from concepts well known in the AI and agent community, as conceptual framework to better understand, modularize, compare and evaluate the individual approaches. We think it is crucial for the design of intelligent systems to focus on the integration and interaction of different learning techniques in one model rather then merging them to create ever new techniques. Two original instantiations of this framework are presented and discussed. Their performance is evaluated for prefetching of bulk data over wireless media

User-Centered Context-Aware Mobile Applications―The Next Generation of Personal Mobile Computing

Context-aware mobile applications are systems that can sense clues about the situational environment and enable appropriate mechanisms of interaction between end users and systems, making mobile devices more intelligent, adaptive, and personalized. In order to better understand such systems and the potentials and barriers of their development and practical use, this paper provides a state-of-the-art overview of this emerging field. Unlike previous literature reviews that mainly focus on technological aspects of such systems, we examine this field mainly from application and research methodology perspectives. We will present major types of current context-aware mobile applications, and discuss research methodologies used in existing studies and their limitations, and highlight potential future research

Preface

These are the proceedings of the 3rd International Conference on Intelligent Technologies for Interactive Entertainment (INTETAIN 09). The first edition of this conference, organised in Madonna di Campiglio, saw the gathering of a diverse audience with broad and varied interests. With presentations on topics ranging from underlying technology to intelligent interaction and entertainment applications, several inspiring invited lectures, a demonstration session and a hands-on design garage, that first edition of INTETAIN generated a lot of interaction between participants in a lively atmosphere. We hope that we have managed to continue this direction with the third edition, which will take place in Amsterdam, following the second edition held in Cancun. The submissions for short and long papers this year show a certain focus on topics such as emergent games, exertion interfaces and embodied interaction, but also cover important topics of the previous editions, such as, affective user interfaces, story telling, sensors, tele-presence in entertainment, animation, edutainment, and (interactive) art. The presentation of the accepted papers, together with the many interactive demonstrations of entertainment and art installations, and other participative activities to be held during the conference, should go some way towards recreating the open and interactive atmosphere that has been the goal of INTETAIN since its beginning. In addition to the aforementioned papers and demonstrations, we are happy to present contributions from three excellent invited speakers for INTETAIN 09. Matthias Rauterberg of Eindhoven University, in his contribution titled “Entertainment Computing, Social Transformation and the Quantum Field��?, takes a broad view as he discusses positive aspects of entertainment computing regarding its capacity for social transformation. Michael Mateas, of the University of California, Santa Cruz, talks about his work in interactive art and storytelling. Antonio Camurri, of InfoMus Lab, Genova, discusses an approach to Human Music Interaction that assigns a more active role to users listening to and interacting with music, in his contribution titled “Non-verbal full body emotional and social interaction: a case study on multimedia systems for active music listening��?