514 research outputs found
Foreground Segmentation of Live Videos Using Boundary Matting Technology
This paper proposes an interactive method to extract foreground objects from live videos using Boundary Matting Technology. An initial segmentation consists of the primary associated frame of a ?rst and last video sequence. Main objective is to segment the images of live videos in a continuous manner. Video frames are 1st divided into pixels in such a way that there is a need to use Competing Support Vector Machine (CSVM) algorithm for the classi?cation of foreground and background methods. Accordingly, the extraction of foreground and background image sequences is done without human intervention. Finally, the initial frames which are segmented can be improved to get an accurate object boundary. The object boundaries are then used for matting these videos. Here an effectual algorithm for segmentation and then matting them is done for live videos where dif?cult scenarios like fuzzy object boundaries have been established. In the paper we generate Support Vector Machine (CSVMs) and also algorithms where local color distribution for both foreground and background video frames are used
General Dynamic Scene Reconstruction from Multiple View Video
This paper introduces a general approach to dynamic scene reconstruction from
multiple moving cameras without prior knowledge or limiting constraints on the
scene structure, appearance, or illumination. Existing techniques for dynamic
scene reconstruction from multiple wide-baseline camera views primarily focus
on accurate reconstruction in controlled environments, where the cameras are
fixed and calibrated and background is known. These approaches are not robust
for general dynamic scenes captured with sparse moving cameras. Previous
approaches for outdoor dynamic scene reconstruction assume prior knowledge of
the static background appearance and structure. The primary contributions of
this paper are twofold: an automatic method for initial coarse dynamic scene
segmentation and reconstruction without prior knowledge of background
appearance or structure; and a general robust approach for joint segmentation
refinement and dense reconstruction of dynamic scenes from multiple
wide-baseline static or moving cameras. Evaluation is performed on a variety of
indoor and outdoor scenes with cluttered backgrounds and multiple dynamic
non-rigid objects such as people. Comparison with state-of-the-art approaches
demonstrates improved accuracy in both multiple view segmentation and dense
reconstruction. The proposed approach also eliminates the requirement for prior
knowledge of scene structure and appearance
Realtime Dynamic 3D Facial Reconstruction for Monocular Video In-the-Wild
With the increasing amount of videos recorded using 2D mobile cameras, the technique for recovering the 3D dynamic facial models from these monocular videos has become a necessity for many image and video editing applications. While methods based parametric 3D facial models can reconstruct the 3D shape in dynamic environment, large structural changes are ignored. Structure-from-motion methods can reconstruct these changes but assume the object to be static. To address this problem we present a novel method for realtime dynamic 3D facial tracking and reconstruction from videos captured in uncontrolled environments. Our method can track the deforming facial geometry and reconstruct external objects that protrude from the face such as glasses and hair. It also allows users to move around, perform facial expressions freely without degrading the reconstruction quality
Moving object detection and segmentation in urban environments from a moving platform
This paper proposes an effective approach to detect and segment moving objects from two time-consecutive stereo frames, which leverages the uncertainties in camera motion estimation and in disparity computation. First, the relative camera motion and its uncertainty are computed by tracking and matching sparse features in four images. Then, the motion likelihood at each pixel is estimated by taking into account the ego-motion uncertainty and disparity in computation procedure. Finally, the motion likelihood, color and depth cues are combined in the graph-cut framework for moving object segmentation. The efficiency of the proposed method is evaluated on the KITTI benchmarking datasets, and our experiments show that the proposed approach is robust against both global (camera motion) and local (optical flow) noise. Moreover, the approach is dense as it applies to all pixels in an image, and even partially occluded moving objects can be detected successfully. Without dedicated tracking strategy, our approach achieves high recall and comparable precision on the KITTI benchmarking sequences.This work was carried out within the framework of the Equipex ROBOTEX (ANR-10- EQPX-44-01). Dingfu Zhou was sponsored by the China Scholarship Council for 3.5 year’s PhD study at HEUDIASYC laboratory in University of Technology of Compiegne
Application of augmented reality and robotic technology in broadcasting: A survey
As an innovation technique, Augmented Reality (AR) has been gradually deployed in the broadcast, videography and cinematography industries. Virtual graphics generated by AR are dynamic and overlap on the surface of the environment so that the original appearance can be greatly enhanced in comparison with traditional broadcasting. In addition, AR enables broadcasters to interact with augmented virtual 3D models on a broadcasting scene in order to enhance the performance of broadcasting. Recently, advanced robotic technologies have been deployed in a camera shooting system to create a robotic cameraman so that the performance of AR broadcasting could be further improved, which is highlighted in the paper
A Game Engine as a Generic Platform for Real-Time Previz-on-Set in Cinema Visual Effects
International audienceWe present a complete framework designed for film production requiring live (pre) visualization. This framework is based on a famous game engine, Unity. Actually, game engines possess many advantages that can be directly exploited in real-time pre-vizualization, where real and virtual worlds have to be mixed. In the work presented here, all the steps are performed in Unity: from acquisition to rendering. To perform real-time compositing that takes into account occlusions that occur between real and virtual elements as well as to manage physical interactions of real characters towards virtual elements, we use a low resolution depth map sensor coupled to a high resolution film camera. The goal of our system is to give the film director's creativity a flexible and powerful tool on stage, long before post-production
- …