Video object segmentation is important for video surveillance, object tracking, video object recognition and video editing. An adaptive video segmentation algorithm based on hidden conditional random fields (HCRFs) is proposed, which models spatio-temporal constraints of video sequence. In order to improve the segmentation quality, the weights of spatio-temporal con- straints are adaptively updated by on-line learning for HCRFs. Shadows are the factors affecting segmentation quality. To separate foreground objects from the shadows they cast, linear transform for Gaussian distribution of the background is adopted to model the shadow. The experimental results demonstrated that the error ratio of our algorithm is reduced by 23% and 19% respectively, compared with the Gaussian mixture model (GMM) and spatio-temporal Markov random fields (MRFs).
CHU Yi-ping YE Xiu-zi QIAN Jiang ZHANG Yin ZHANG San-yuan
The emergence of third generation mobile system (3G) makes video transmission in wireless environment possible, and the latest 3GPP/3GPP2 standards require 3G terminals support H.264/AVC. Due to high packet loss rate in wireless envi- ronment, error resilience for 3G terminals is necessary. Moreover, because of the hardware restrictions, 3G mobile terminals support only part of H.264/AVC error resilience tool. This paper analyzes various error resilience tools and their functions, and presents 2 error resilience strategies for 3G mobile streaming video services and mobile conversational services. Performances of the proposed error resilience strategies were tested using off-line common test conditions. Experiments showed that the proposed error resilience strategies can yield reasonably satisfactory results.
With the rapid development of 3D digital photography and 3D digital scanning devices, massive amount of point samples can be generated in acquisition of complex, real-world objects, and thus create an urgent need for advanced point-based processing and editing. In this paper, we present an interactive method for blending point-based geometries by dragging-and- dropping one point-based model onto another model’s surface metaphor. We first calculate a blending region based on the polygon of interest when the user drags-and-drops the model. Radial basis function is used to construct an implicit surface which smoothly interpolates with the transition regions. Continuing the drag-and-drop operation will make the system recalculate the blending regions and reconstruct the transition regions. The drag-and-drop operation can be compound in a constructive solid geometry (CSG) manner to interactively construct a complex point-based model from multiple simple ones. Experimental results showed that our method generates good quality transition regions between two raw point clouds and can effectively reduce the rate of overlapping during the blending.
An approach for generating interactive 3D graphical visualization of the genetic architectures of complex traits in multiple environments is described. 3D graphical visualization is utilized for making improvements on traditional plots in quan- titative trait locus (QTL) mapping analysis. Interactive 3D graphical visualization for abstract expression of QTL, epistasis and their environmental interactions for experimental populations was developed in framework of user-friendly software QTLNetwork (http://ibi.zju.edu.cn/software/qtlnetwork). Novel definition of graphical meta system and computation of virtual coordinates are used to achieve explicit but meaningful visualization. Interactive 3D graphical visualization for QTL analysis provides geneticists and breeders a powerful and easy-to-use tool to analyze and publish their research results.
HU Cheng-chengYE Xiu-ziZHANG YinYU Rong-dongYANG JianZHU Jun
