Stereoscopic Seam Carving With Temporal Consistency

In this paper, we present a novel technique for seam carving of stereoscopic video. It removes seams of pixels in areas that are most likely not noticed by the viewer. When applying seam carving to stereoscopic video rather than monoscopic still images, new challenges arise. The detected seams must be consistent between the left and the right view, so that no depth information is destroyed. When removing seams in two consecutive frames, temporal consistency between the removed seams must be established to avoid flicker in the resulting video. By making certain assumptions, the available depth information can be harnessed to improve the quality achieved by seam carving. Assuming that closer pixels are more important, the algorithm can focus on removing distant pixels first. Furthermore, we assume that coherent pixels belonging to the same object have similar depth. By avoiding to cut through edges in the depth map, we can thus avoid cutting through object boundaries

Future Directions in Astronomy Visualisation

Despite the large budgets spent annually on astronomical research equipment such as telescopes, instruments and supercomputers, the general trend is to analyse and view the resulting datasets using small, two-dimensional displays. We report here on alternative advanced image displays, with an emphasis on displays that we have constructed, including stereoscopic projection, multiple projector tiled displays and a digital dome. These displays can provide astronomers with new ways of exploring the terabyte and petabyte datasets that are now regularly being produced from all-sky surveys, high-resolution computer simulations, and Virtual Observatory projects. We also present a summary of the Advanced Image Displays for Astronomy (AIDA) survey which we conducted from March-May 2005, in order to raise some issues pertitent to the current and future level of use of advanced image displays.Comment: 13 pages, 2 figures, accepted for publication in PAS

Panoramic Human Structure Maintenance based on Invariant Features of Video Frames

[[abstract]]Panoramic photography is becoming a very popular and commonly available feature in the mobile handheld devices nowadays. In traditional panoramic photography, the human structure often becomes messy if the human changes position in the scene or during the combination step of the human structure and natural background. In this paper, we present an effective method in panorama creation to maintain the main structure of human in the panorama. In the proposed method, we use an automatic method of feature matching, and the energy map of seam carving is used to avoid the overlapping of human with the natural background. The contributions of this proposal include automated panoramic creation method and it solves the human ghost generation problem in panorama by maintaining the structure of human by energy map. Experimental results prove that the proposed system can be effectively used to compose panoramic photographs and maintain human structure in panorama.[[incitationindex]]SCI[[booktype]]電子

Image stitching algorithm based on feature extraction

This paper proposes a novel edge-based stitching method to detect moving objects and construct\ud mosaics from images. The method is a coarse-to-fine scheme which first estimates a\ud good initialization of camera parameters with two complementary methods and then refines\ud the solution through an optimization process. The two complementary methods are the edge\ud alignment and correspondence-based approaches, respectively. The edge alignment method\ud estimates desired image translations by checking the consistencies of edge positions between\ud images. This method has better capabilities to overcome larger displacements and lighting variations\ud between images. The correspondence-based approach estimates desired parameters from\ud a set of correspondences by using a new feature extraction scheme and a new correspondence\ud building method. The method can solve more general camera motions than the edge alignment\ud method. Since these two methods are complementary to each other, the desired initial estimate\ud can be obtained more robustly. After that, a Monte-Carlo style method is then proposed for\ud integrating these two methods together. In this approach, a grid partition scheme is proposed to\ud increase the accuracy of each try for finding the correct parameters. After that, an optimization\ud process is then applied to refine the above initial parameters. Different from other optimization\ud methods minimizing errors on the whole images, the proposed scheme minimizes errors only on\ud positions of features points. Since the found initialization is very close to the exact solution and\ud only errors on feature positions are considered, the optimization process can be achieved very\ud quickly. Experimental results are provided to verify the superiority of the proposed method

On Sensor-Controlled Robotized One-off Manufacturing

A semi-automatic task oriented system structure has been developed and tested on an arc welding application. In normal industrial robot programming, the path is created and the process is based upon the decided path. Here a process-oriented method is proposed instead. It is natural to focus on the process, since the path is in reality a result of process needs. Another benefit of choosing process focus, is that it automatically leads us into task oriented thoughts, which in turn can be split in sub-tasks, one for each part of the process with similar process-characteristics. By carefully choosing and encapsulating the information needed to execute a sub-task, this component can be re-used whenever the actual subtask occurs. By using virtual sensors and generic interfaces to robots and sensors, applications built upon the system design do not change between simulation and actual shop floor runs. The system allows a mix of real- and simulated components during simulation and run-time