31 research outputs found
Optimal packetisation of MPEG-4 using RTP over mobile networks
The introduction of third-generation wireless networks should result in real-time mobile
video communications becoming a reality. Delivery of such video is likely to be facilitated by the realtime
transport protocol (RTP). Careful packetisation of the video data is necessary to ensure the
optimal trade-off between channel utilisation and error robustness. Theoretical analyses for two basic
schemes of MPEG-4 data encapsulation within RTP packets are presented. Simulations over a GPRS
(general packet radio service) network are used to validate the analysis of the most efficient scheme.
Finally, a motion adaptive system for deriving MPEG-4 video packet sizes is presented. Further
simulations demonstrate the benefits of the adaptive system
Model design for scalable 2-D model-based video coding
3D face synthesis has been extensively used in many applications over the last decade. Although many methods have been reported, automatic 3D face synthesis from a single video frame still remains unsolved. An automatic 3D face synthesis algorithm is proposed, which resolves a number of existing bottlenecks
Anisotropic mean shift based fuzzy c-means segmentation of deroscopy images
Image segmentation is an important task in analysing dermoscopy images as the extraction of the borders of skin lesions provides important cues for accurate diagnosis. One family of segmentation algorithms is based on the idea of clustering pixels with similar characteristics. Fuzzy c-means has been shown to work well for clustering based segmentation, however due to its iterative nature this approach has excessive computational requirements. In this paper, we introduce a new mean shift based fuzzy c-means algorithm that requires less computational time than previous techniques while providing good segmentation results. The proposed segmentation method incorporates a mean field term within the standard fuzzy c-means objective function. Since mean shift can quickly and reliably find cluster centers, the entire strategy is capable of effectively detecting regions within an image. Experimental results on a large dataset of diverse dermoscopy images demonstrate that the presented method accurately and efficiently detects the borders of skin lesions
