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Cameron Smith

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5 papers
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5

NeurIPS Conference 2023 Conference Paper

FlowCam: Training Generalizable 3D Radiance Fields without Camera Poses via Pixel-Aligned Scene Flow

  • Cameron Smith
  • Yilun Du
  • Ayush Tewari
  • Vincent Sitzmann

Reconstruction of 3D neural fields from posed images has emerged as a promising method for self-supervised representation learning. The key challenge preventing the deployment of these 3D scene learners on large-scale video data is their dependence on precise camera poses from structure-from-motion, which is prohibitively expensive to run at scale. We propose a method that jointly reconstructs camera poses and 3D neural scene representations online and in a single forward pass. We estimate poses by first lifting frame-to-frame optical flow to 3D scene flow via differentiable rendering, preserving locality and shift-equivariance of the image processing backbone. SE(3) camera pose estimation is then performed via a weighted least-squares fit to the scene flow field. This formulation enables us to jointly supervise pose estimation and a generalizable neural scene representation via re-rendering the input video, and thus, train end-to-end and fully self-supervised on real-world video datasets. We demonstrate that our method performs robustly on diverse, real-world video, notably on sequences traditionally challenging to optimization-based pose estimation techniques.

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AAMAS Conference 2017 Conference Paper

An Interactive Narrative Platform for Story Understanding Experiments

  • Julie Porteous
  • Fred Charles
  • Cameron Smith
  • Marc Cavazza
  • Jolien Mouw
  • Paul van den Broek

Interactive Narratives are systems that use automated narrative generation techniques to create multiple story variants which can be shown to an audience, as virtual narratives, using cinematic staging techniques. The focus of previous research has included aspects such as the quality of automatically generated narratives and the way in which audiences respond to them. However in this work we have developed a mechanism for control of interactive narratives that supports their use in experiments to assess story understanding. This is implemented in our demonstration system, which features two parts: an interface that allows high-level specification of criteria for story understanding experiments; and a participant interface in which virtual narratives, conforming to the experimental design, are presented as 3D visualizations. The virtual narrative is based on a pre-existing children’s story, and features a cast of virtual characters.

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AAMAS Conference 2017 Conference Paper

Using Virtual Narratives to Explore Children's Story Understanding

  • Julie Porteous
  • Fred Charles
  • Cameron Smith
  • Marc Cavazza
  • Jolien Mouw
  • Paul van den Broek

Interactive Narratives are systems that use automated narrative generation techniques to create multiple story variants which can be shown to an audience, as virtual narratives, using cinematic staging techniques. Previous research in this area has focused on assessment of aspects such as the quality of the automatically generated narratives and their acceptance by the audience. However in our work we deviate from this to explore the use of interactive narratives to support cognitive psychology experiments in story understanding. We hypothesized that the use of virtual narratives would enable narrative comprehension to be studied independently of linguistic phenomena. To assess this we developed a demonstration interactive narrative featuring a virtual environment (Unity3D engine) based on a pre-existing children’s story which allows for the generation of variants of the original story that can be "told" via visualization in the 3D world. In the paper we introduce a narrative generation mechanism that provides control over insertion of cues facilitating story understanding, whilst also ensuring that the plot itself is unaffected. An intuitive user interface allows experimenters to insert and order cues and specific events while the narrative generation techniques ensure these requests are effected in a consistent fashion. We also report the results of a field experiment with children (age 9-10) that demonstrates the potential for the use of virtual narratives in story understanding experiments. Our results demonstrated acceptance of virtual narratives, the usability of the system and the impact of cue insertion on inference and story understanding.

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AAMAS Conference 2008 Conference Paper

A �Companion' ECA with Planning and Activity Modelling

  • Marc Cavazza
  • Cameron Smith
  • Daniel Charlton
  • Li Zhang
  • Jaakko Hakulinen
  • Markku Turunen

In this paper, we describe the development of an Embodied Conversational Agent (ECA) implementing the concept of a companion, i. e. an agent supporting the persistent representation of user activities and dialogue-based communication with the user. This first experiment implements a Health and Fitness companion aimed at promoting a healthier lifestyle. The system operates by generating an ‘ideal’ plan of daily activities from background knowledge and dialogue interaction with the user. This plan then becomes an activity model, which will later be instantiated by reports from the user and analysed by the agent from the perspective of initial objectives. At various stages of the day, the plan can still be adapted through further dialogue. The agent is embodied using a wireless rabbit (Nabaztag™) device situated in the user’s home. After describing the planning component, based on Hierarchical Task Networks (HTN) and the spoken dialogue system, we present a working example from the system illustrating its behaviour through various phases of user activity generation, updating and re-planning.

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AAMAS Conference 2008 Conference Paper

An Embodied Conversational Agent as a Lifestyle Advisor

  • Cameron Smith
  • Daniel Charlton
  • Li Zhang
  • Jaakko Hakulinen
  • Markku Turunen
  • Marc Cavazza

Persistent Embodied Conversational Agents (ECA) can be used to assist users in their daily activities. We introduce the Health and Fitness Companion (HFC), which is a conversational system aimed at promoting a healthier lifestyle. The system is embodied using the NabaztagTM device, a wireless plastic rabbit supporting multimodal input and output. The HFC integrates a spoken dialogue system previously developed by some of the authors, and a cognitive model, based on Hierarchical Task Network (HTN) planning, which enables the ECA to reason on the user activities and generate plans for recommended activities. A typical demonstration scenario consists in two short conversation sessions between the HFC and the user. During the first the HFC helps the user to plan her day ahead, while the second involves reporting the activities actually carried out. The system has undergone early tests with generic users, which have demonstrated its usability and stability (89% successful dialogue completions).

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