A video cut detector (CD), a member of the shot boundary detector (SBD) group, is an essential element for spatio-temporal audiovisual (AV) segmentation and various video-processing technologies. Platform, processing and performance constraints forced the development of various dedicated CDs. Future platforms allow the usage of advanced CD algorithms with higher reliability. In order to enable an appropriate trade-off decision to be made between reliability and the required processing power, benchmarking of four CD algorithms has taken place on bases of a generic, culture-diverse multi-genre AV corpus. In terms of complexity/performance trade-off, a field-difference-based CD proved to be optimal.

The gap between application specific integrated circuits (ASICs) and general-purpose programmable processors in terms of performance, power, cost and flexibility is well known. Application specific instruction-set processors (ASIPs) bridge this gap. In this work, we demonstrate the key benefits of ASIPs for several video applications. One of the most compute- and memory-intensive functions in video processing is motion estimation (ME). The focus of this work is on the design of a ME template, which is useful for several video applications like video encoding, obstacle detection, picturerate up-conversion, 2-D-to-3-D video conversion, etc. An instruction-set suitable for performing a variety of ME functions is developed. The ASIP is based on a very long instruction word (VLIW) processor template and meets low-power and low-cost requirements still providing the flexibility needed for the application domain. The ME ASIP design consumes 27 mW and takes an area of 1.1 mm/sup 2/ in 0.13 /spl mu/m technology performing picturerate up-conversion, for standard definition (CCIR601) resolution at 50 frames per second.

We present a method for improving the temporal stability of video object segmentation algorithms for 3D-TV applications. First, two quantitative measures to evaluate temporal stability without ground-truth are presented. Then, a pseudo-3D curve evolution method, which spatio-temporally stabilizes the estimated object segments is introduced. Temporal stability is achieved by re-distributing existing object segmentation errors such that they are less disturbing when the scene is rendered and viewed in 3D. Our starting point is the hypothesis that if making segmentation errors are inevitable, they should be made in a temporally consistent way for 3D TV applications. This hypothesis is supported by the experiments, which show that there is significant improvement in segmentation quality both in terms of the objective quantitative measures and in terms of the viewing comfort in subjective perceptual tests. This shows that it is possible to increase the object segmentation quality without increasing the actual segmentation accuracy.