2010 IEEE International Conference on Image Processing

Video editing plays an important role in today's cinematic post-production: editing operations are typically applied on a keyframe basis and propagated automatically to the rest of the sequence. Thereby, small inconsistencies in correspondences used for the propagation of editing operations accumulate and need to be corrected manually. The amount of required manual interaction increases further wh... View full abstract»

The 3-D shape perceived from viewing a stereoscopic movie depends on the viewing conditions, most notably on the screen size and distance, and depth and size distortions appear because of the differences between the shooting and viewing geometries. When the shooting geometry is constrained, or when the same stereoscopic movie must be displayed with different viewing geometries (e.g. in a movie the... View full abstract»

Conventional stereoscopic video content production requires use of dedicated stereo camera rigs which is both costly and lacking video editing flexibility. In this paper, we propose a novel approach which only requires a small number of standard cameras sparsely located around a scene to automatically convert the monocular inputs into stereoscopic streams. The approach combines a probabilistic spa... View full abstract»

Reconstructing the 3D shape of human faces is an intensively researched topic. Most approaches aim at generating a closed surface representation of geometry, i.e. a mesh, which is texture-mapped for rendering. However, if free viewpoint rendering is the primary purpose of the reconstruction, representations other than meshes are possible. In this paper a coarse patch-based approach to both reconst... View full abstract»

Many published machine vision algorithms are designed to be real-time and fully automatic with low computational complexity. These attributes are essential for applications such as stereo robotic vision. Motion Picture Digital Visual Effect facilities, however, have massive computation resources available and can afford human interaction to initialise algorithms and to guide them towards a good so... View full abstract»

Depth maps are becoming a readily available commodity of the stereo pipeline. We propose to make use of this new free information to improve a key step of postproduction that is matting. We extend the work of Levin et al on closed form matting to introduce two new depth-aware techniques. First we explore how depth can be used as an extra channel in the matting process. Then we see how depth can be... View full abstract»

We present a novel approach that achieves segmentation of subject body parts in 3D videos. 3D video consists in a free-viewpoint video of real-world subjects in motion immersed in a virtual world. Each 3D video frame is composed of one or several 3D models. A topology dictionary is used to cluster 3D video sequences with respect to the model topology and shape. The topology is characterized using ... View full abstract»

The aim of this paper is to present a new method for multiview object or human body (or body part) detection. The basic idea consists of using a single view detector in every view of a scene captured by multiple cameras and then combining the results using the 3D information of the scene. The method can improve the results of the single view detector, while also localizing the object/human in the ... View full abstract»

A new scheme for back-projection of weights for mean shift based object tracking is proposed. Weights are calculated based on relative counts of histogram bins for each feature used in similarity assessment. A fusion scheme is proposed to combine the back-projected weights from different features, such that the dissimilarities between the object being tracked and the background are boosted. A mech... View full abstract»

This paper proposes a distributed algorithm for object tracking in a camera sensor network. At each camera node, an efficient online multiple instance learning algorithm is used to model object's appearance. This is integrated with particle filter for camera's image plane tracking. To improve the tracking accuracy, each camera node shares its particle states with others and fuses multi-camera info... View full abstract»

This paper presents a data-oriented tracking framework which aims to recover the spatio-temporal trajectories for an unknown number of interacting objects appearing and disappearing at arbitrary times. Data association is performed at three-levels of a hierarchy: (i) first, trajectory segments and an associated quality measure are generated by a local analysis of the space-time distribution of obs... View full abstract»

Object tracking through particle filtering has been widely addressed in recent years. However, most works assume a constant number of objects or utilize an external detector that monitors the entry or exit of objects in the scene. In this work, a novel tracking method based on particle filtering that is able to automatically track a variable number of objects is presented. As opposed to classical ... View full abstract»

We formulate parametric curve fitting as a concave cost minimization problem. Our formulation is general encompassing any parametric curve where parameters can be free or constrained. The proposed concave cost opens the future possibility of applying several available concave programming algorithms in curve fitting. In this paper, we propose a fast local minimization of the concave cost and utiliz... View full abstract»

Maintaining the stability of tracks on multiple targets in video over extended time periods remains a challenging problem. A few methods which have recently shown encouraging results in this direction rely on learning context models or the availability of training data. However, this may not be feasible in many application scenarios. Moreover, tracking methods should be able to work across multipl... View full abstract»

Efficient visual object detection is of central interest in computer vision and pattern recognition due to its wide ranges of applications. Viola and Jones' detector has become a de facto framework [1]. In this work, we propose a new method to design a cascade of boosted classifiers for fast object detection, which combines linear asymmetric classification (LAC) into the recent multi-exit cascade ... View full abstract»

Based on the theory of Markov Random Fields, a Bayesian regularization model for diffusion tensor images (DTI) is proposed in this paper. The low-degree parameterization of diffusion tensors in our model makes it less computationally intensive to obtain a maximum a posteriori (MAP) estimation. An approximate solution to the problem is achieved efficiently using hierarchical Markov Chain Monte Carl... View full abstract»

Synthetic aperture radar (SAR), ultrasound-B, laser, and sonar imagery are contaminated with speckle noise. The statistical modelling of such contamination is well described by the multiplicative model, which yields the G0distribution. In particular, reliable image contrast measures are sought in order to discriminate targets. To that end, we present statistical methods based on stochas... View full abstract»

Discovering local geometry of low-dimensional manifold embedded into a high-dimensional space has been widely studied in the literature of machine learning. Counter-intuitively, we will show for the class of signal-independent additive noise, noisy data do not destroy the manifold structure thanks to the blessing of dimensionality. Based on this observation, we propose to reconstruct the manifold ... View full abstract»