Intuitive and efficient camera control with the toric space

Abstract

1 2 3 4 5 7 6The Toric space model For computing viewpoints For manipulating viewpoints For interpolating viewpoints Figure 1: We present (a) the Toric space, a novel and compact representation for intuitive and efficient virtual camera control. We demonstrate the potential of this representation by proposing (b) an efficient automated viewpoint computation technique, (c) a novel and intuitive screenspace manipulation tool, and (d) an effective viewpoint interpolation technique. AbstractA large range of computer graphics applications such as data visualization or virtual movie production require users to position and move viewpoints in 3D scenes to effectively convey visual information or tell stories. The desired viewpoints and camera paths are required to satisfy a number of visual properties (e.g. size, vantage angle, visibility, and on-screen position of targets). Yet, existing camera manipulation tools only provide limited interaction methods and automated techniques remain computationally expensive.In this work, we introduce the Toric space, a novel and compact representation for intuitive and efficient virtual camera control. We first show how visual properties are expressed in this Toric space and propose an efficient interval-based search technique for automated viewpoint computation. We then derive a novel screen-space manipulation technique that provides intuitive and real-time control of visual properties. Finally, we propose an effective viewpoint interpolation technique which ensures the continuity of visual properties along the generated paths. The proposed approach (i) performs better than existing automated viewpoint computation techniques in terms of speed and precision, (ii) provides a screen-space manipulation tool that is more efficient than classical manipulators and easier to use for beginners, and (iii) enables the creation of complex camera motions such as long takes in a very short time and in a controllable way. As a result, the approach should quickly find its place in a number of applications that require interactive or automated camera control such as 3D modelers, navigation tools or 3D games.

Autonomous aerial cinematography in unstructured environments with learned artistic decision‐making

“…These methods typically reason about the utility of a viewpoint in isolation, follow artistic principles and composition rules (Arijon, ; Bowen & Thompson, ) and employ either optimization‐based approaches to find good viewpoints or reactive approaches to track the virtual actor. The focus is typically on through‐the‐lens control where a virtual camera is manipulated while maintaining focus on certain image features (Drucker & Zeltzer, ; Gleicher & Witkin, ; Lino & Christie, ; Lino, Christie, Ranon, & Bares, ). However, virtual cinematography is free of several real‐world limitations such as robot physics constraints and assumes full knowledge of the environment.…”

Towards a Robust Aerial Cinematography Platform: Localizing and Tracking Moving Targets in Unstructured Environments

“…These methods tend to reason about the utility of a viewpoint in isolation, following artistic principles and composition rules [10], [11] and employ either optimization-based approaches to find good viewpoints, or reactive approaches to track the virtual actor. The focus is typically on through-the-lens control where a virtual camera is manipulated while maintaining focus on certain image features [12]- [15]. However, virtual cinematography is free of several real-world limitations such as robot physics constraints and assumes full map knowledge.…”

On Realistic Target Coverage by Autonomous Drones

“…Figure 8 shows two examples of AOV circle pairs. In concurrent work, an alternative approach to covering pairs of targets was developed in (Lino and Christie 2015); using Euler angles to parameterize the set of camera placements yielding a speci c on-screen composition of the given pair of targets, the best viewpoint is found by an interval-based search in the parametric space de ned by the Euler angles. In contrast, our approach works directly in the Cartesian space of camera placements yielding a more intuitive spatial decomposition which is easier to incorporate with the other constraints we consider for the purposes of coverage as required in surveillance and similar applications.…”