Efficient camera path planning algorithm for human motion overview

Abstract

Camera path planning for character motions is a fundamental and important research topic, benefiting many animation applications. Existing optimal-based approaches are generally computationally expensive and infeasible for interactive applications. In this paper, we propose an efficient approach that can take many constraints of finding the camera path into account and can potentially enable interactive camera control. Instead of solving a highly complicated camera optimization problem in a spatiotemporal four-dimensional space, we heuristically determine the camera path based on an efficient greedy-based tree traversal approach. The experimental results show that the proposed approach can efficiently generate a smooth, informative, and aesthetic camera path that can reveal the significant features of character motions. Moreover, the conducted user study also shows that the generated camera paths are comparable to those of a state-of-the-art approach and those made by professional animators.

Intuitive and efficient camera control with the toric space

“…Assa et al [2008] propose an offline method based on the maximization, through a simulated annealing algorithm, of a viewpoint entropy (measuring how much of a single target's motion project onto the screen) along time while ensuring the camera path smoothness in terms of speed, acceleration and change in orientation. Yeh et al [2011] improve the viewpoint entropy, and the search efficiency by using multiple A*-based searches and a backtracking mechanism.…”

Optimal Control to Support High-Level User Goals in Human-Computer Interaction

“…In research, the planning of physically feasible quadrotor camera trajectories has recently received a lot of attention. Design tools allow for planning of aerial shots in 3D virtual environments (Gebhardt et al, 2016;Joubert et al, 2015;Xie et al, 2018) and employ optimization to ensure that aesthetic objectives and robot modeling constraints are satisfied. An extension of these tools helps users to stay within the feasible range of quadrotor motion .…”

“…This approach automates the framing of camera targets and, hence, does not leave compositional control to users. Similarly, Xie et al, 2018 propose an optimization-based approach that requires user to only specify a quadrotor's start and end position as well as landmarks of interest and then generates a trajectory utilizing a landmark-centric view quality field. The view field optimizes the camera orientation such that the salient parts of landmarks are positioned on the image plane according the Rules of Thirds.…”

Optimizing for aesthetically pleasing quadrotor camera motion

“…Camera Control in Virtual Environments: Camera placement [Lino and Christie 2012], path planning [Li and Cheng 2008;Yeh et al 2011] and automated cinematography [Lino et al 2011] have been studied extensively in virtual environments (VE), for a survey see [Christie et al 2008]. These works share our goal of assisting users in the creation of camera motion (e.g., [Drucker and Zeltzer 1994;Lino and Christie 2015]).…”