42801293
Evaluation of an ultra-wide bandwidth wireless indoor non-line-of-sight channels
35950271
Partition Triangle Meshes into Coarsely Quadrangular Segmentation
A feature captured approach was presented to automatically partition a triangle meshes into a coarsely quadrangular segmentation. The triangle meshes was firstly partitioned into a polygonal segmentation which was further split into triangular and quadrangular patches. After the convex and concave features were identified, the triangular patches were eliminated according to their topological relations to achieve the quadrangular segmentation. The optimization methods based on globally smooth parameterization and active contour model were also adopted to improve the qualities of quadrangular patches and their edges. The final segmentation consisted of pure-quadrangular patches with appropriate sizes according to the model's geometric characteristics, and the features of input model werewell captured.
18961070
A probabilistic approach for foreground and shadow segmentation in monocular image sequences
This paper presents a novel method of foreground and shadow segmentation in monocular indoor image sequences. The models of background, edge information, and shadow are set up and adaptively updated. A Bayesian network is proposed to describe the relationships among the segmentation label, background, intensity, and edge information. A maximum a posteriori-Markov random field estimation is used to boost the spatial connectivity of segmented regions.
1173197
Situating Productive Play: Online Gaming Practices and Guanxi in China
Economic activities in and around online gaming in China are often correlated in the West with practices of gold farming, or selling in-game currency to players for real money in online games. What can we learn about online gaming in China and about online gaming and online sociality more broadly when we look at economic and other "pragmatic" practices through which online gaming becomes meaningful to players? In this paper, we present findings from an ethnographic study of online gaming in China's urban Internet cafes to discuss implications for game design, and HCI design more broadly. Considering the ties between socio-economic practices, development of trust and culturally situated imaginings of self-hood and otherness, brings to the fore how online gaming in and of itself constitutes the means for practical achievements in day-to-day management of guanxi (social connection).
2407307
Dynamictrust: the trust development in peer-to-peer environments
In peer-to-peer (P2P) environments, trust is a very important issue when transactions/interactions occur between peers. In general, the trust evaluation on transactions/interactions relies on the recommendations from other peers, which may be inaccurate. This paper presents Dynamictrust, a P2P trust evaluation system. It is based on our peer trust evaluation model, which measures the credibility of peers' recommendations, and thus filters noise in responses and obtains more accurate and objective trust values
8808466
Joint region tracking with switching hypothesized measurements
We propose a switching hypothesized measurements (SHM) model supporting multimodal probability distributions and present the application of the model in handling potential variability in visual environments when tracking multiple objects jointly. For a set of occlusion hypotheses, a frame is measured once under each hypothesis, resulting in a set of measurements at each time instant. A computationally efficient SHM filter is derived for online joint region tracking. Both occlusion relationships and states of the objects are recursively estimated from the history of hypothesized measurements. The reference image is updated adaptively to deal with appearance changes of the objects. The SHM model is generally applicable to various dynamic processes with multiple alternative measurement methods.
20945105
Real-Time Moving Vehicle Detection With Cast Shadow Removal in Video Based on Conditional Random Field
This paper presents an approach of moving vehicle detection and cast shadow removal for video based traffic monitoring. Based on conditional random field, spatial and temporal dependencies in traffic scenes are formulated under a probabilistic discriminative framework, where contextual constraints during the detection process can be adaptively adjusted in terms of data-dependent neighborhood interaction. Computationally efficient algorithm has been developed to discriminate moving cast shadows and handle nonstationary background processes for real-time vehicle detection in video streams. Experimental results show that the proposed approach effectively fuses contextual dependencies and robustly detects moving vehicles under heavy shadows even in grayscale video.