Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Inserting Synthetic Characters into Live-Action Scenes of Multiple People
CASA '03 Proceedings of the 16th International Conference on Computer Animation and Social Agents (CASA 2003)
ACM SIGGRAPH 2006 Papers
Experiment-based modeling, simulation and validation of interactions between virtual walkers
Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Aggregate dynamics for dense crowd simulation
ACM SIGGRAPH Asia 2009 papers
Technical Section: Continuum crowd simulation in complex environments
Computers and Graphics
Simulating the local behaviour of small pedestrian groups
Proceedings of the 17th ACM Symposium on Virtual Reality Software and Technology
Online Multiperson Tracking-by-Detection from a Single, Uncalibrated Camera
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient use of geometric constraints for sliding-window object detection in video
ICVS'11 Proceedings of the 8th international conference on Computer vision systems
KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera
Proceedings of the 24th annual ACM symposium on User interface software and technology
Pedestrian detection at 100 frames per second
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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In this paper, we propose a novel approach to integrate virtual pedestrians into a scene of real pedestrian groups with behavior consistency, and this is achieved by dynamic path planning of virtual pedestrians. Rather than accounting for the local collision avoidance only, our approach is capable of finding an optimized path for each virtual pedestrian on his way based on the current global distribution of the real groups in the scene. The big challenge is due to the information of both position and velocity of real pedestrians in the video being unavailable; also the distribution of the groups in the scene may vary dynamically. We therefore need to detect and track real pedestrians on each frame of the video to acquire their distribution and motion information. We save this information by an efficient data structure, called environment grid. During the way of a virtual pedestrian, the respective agent frequently emits the detection rays through the environment cells to find the situation of the real pedestrians ahead of him and adjust the original path if necessary. Virtual pedestrians are merged into the video finally with the occlusion between virtual characters and the real pedestrians correctly presented. Experiment results on several scenarios demonstrate the effectiveness of the proposed approach.