This paper presents a new method which allows the artificial creation of cast shadows in the context of video post-production applications for which video objects are inserted in an original video sequence. The manipulated video objects are assumed to have been previously segmented together with their cast shadows in their original images, and to have been inserted in the edited images. This paper deals with the problem of the artificial creation of the corresponding cast shadows. A reference image which represents the scene illuminated background is assumed to be available. The proposed method is based on a precise shadow model and on the use of the 3-D structure of the scene background. This 3-D information is roughly obtained manually in a pre-processing phase. Then, the illumination conditions, i.e. a shadow model and the light source position are estimated. The shape and texture of the created cast shadows are defined by combining geometrical relations linking the light source, the video objects and the cast shadows, and by applying the inverse shadow model to artificially shade the shadow areas. Experimental results show that it is possible to obtain satisfactory visual results.
This paper proposes a new method for the detection of moving cast shadows in natural video sequences. The variations of illumination generate in a shadow area are modelized assuming that the source light is fixed and unique, and that the surface on which the shadow is projected is plane and Lambertian. A local and global matching of this model is then done on the current image in order to obtain a first detection of the moving shadow areas. This matching process is based on a reference image which is assumed to contain no moving shadow. A spatio-temporal follow up of the obtained areas is applied in order to remove false detection. The proposed segmentation method was tested and validated on real video sequences.
We present a new method for the estimation of non-planar rotations, i.e. rotations around axis parallel to the image plane, in the context of video compression applications. This method is based on a non planar rotation model which assumes that the moving objects have a planar surface. The proposed block-based motion estimation approach is performed between consecutive or non-consecutive images, which may be contained large displacements, and aims at minimizing the motion compensation error. The efficiency of the method has been compared to the results obtained with the classical full search block matching approach. Experimental results have been done on real video sequences. These results show a significant gain in term of PSNR for the motion compensated P or B frames, compared to the classical full search block matching approach, while the coding cost of the additional motion information is very low, which demonstrates the interest of the proposed rotation model in the context of motion compensation for video compression applications.
With the emergence of MPEG-4, the new standard for multimedia applications, the mix of natural and synthetic material is made possible and will lead to fast developments of applications in virtual and augmented realities fields such as video special effects or post-processing. Nevertheless, with existing techniques, object-based editing and compositing of real video sequences require important manual processing. The proposed interactive and semi- automatic object-based video editing approach has been designed in order to reduce as much as possible this human work. It is based on key-framing and permits to add new moving objects, and to remove or to modify the trajectories of existing ones. This method has been validated on real test sequences.
KEYWORDS: 3D modeling, Cameras, 3D image processing, Video, Panoramic photography, Calibration, Data modeling, Visualization, Light sources and illumination, Image processing
This paper describes a new method for creating mosaic images from an original video and for computing a new sequence modifying some camera parameters like image size, scale factor, view angle... A mosaic image is a representation of the full scene observed by a moving camera during its displacement. It provides a wide angle of view of the scene from a sequence of images shot with a narrow angle of view camera. This paper proposes a method to create a virtual sequence from a calibrated original video and a rough 3D model of the scene. A 3D relationship between original and virtual images gives pixel correspondent in different images for a same 3D point in model scene. To texture the model with natural textures obtained in the original sequence, a criterion based on constraints related to the temporal variations of the background and 3D geometric considerations is used. Finally, in the presented method, the textured 3D model is used to recompute a new sequence of image with possibly different point of view and camera aperture angle. The algorithm is being proven with virtual sequences and, obtained results are encouraging up to now.
This paper proposes a new methodology to deal with videoconference applications in which several different sties can be involved. In such applications, it should be interesting for each user to watch only one image which gives him the impression that everybody is in the same virtual room. Furthermore, since it can be expected that only a very limited transmission bandwidth is available, it is important to transmit only useful information. For these reasons, we have developed a technique which consists in the creation of a hybrid synthetic/natural scene. This hybrid scene contains the real images of each interlocutor of the multi-sites videoconference. This permits to reduce the bitrate since only the regions of interest contained in the real video data must be coded and transmitted. In practice, the background of the scene, which has generally no interest for users, is not coded. The extraction of these regions of interest is performed of the scene, which has generally no interest for users, is not coded. The extraction of these regions of interest is performed by a new detection algorithm based on a reference image. In order to manage occlusion and collision problems in the hybrid images, a 3D positioning strategy of 2D real objects has been developed. Experimental results are presented on real videoconference- like image sequences.
Motion estimation and compensation techniques are widely used in video coding. This paper addresses the problem of the trade-off between the motion and the prediction error information. Under some realistic hypotheses, the transmission cost of these two components can be estimated. Therefore, we obtain a criterion which controls the motion estimation process in order to optimize its performance. As a particular application, this criterion is applied to the split procedure of an adaptive multigrid block matching technique. Simulation results are presented, showing the significant improvements due to the method.
This paper introduces an improved variable size block based motion estimation algorithm relying on a hierarchy of motion representations. The most efficient of the latter is chosen through an evaluation constraint which models the total bit rate. The proposed coding technique exploits the concepts of temporal tracking and localization of the displaced frame difference energy. Moreover, only the smallest regions of the latter are coded and transmitted. Simulations show a significant improvement of the performances.
For dynamic scene analysis [HOR81],[ADI85],[HAR85], numerous studies developped derivation methods of qualitative motion features from a dense apparent velocity vector field (optical flow). However, these qualitative information [FRA90] can not be used for image sequence reconstruction because no explicit reconstruction criterion is introduced within the feature identification process itself.
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