18329174
Enhancing 3D Graphics on Mobile Devices by Image-Based Rendering
Compared to a personal computer, mobile devices typically have weaker processing power, less memory capacity, and lower resolution of display. While the former two factors are clearly disadvantages for 3D graphics applications running on mobile devices, the display factor could be turned into an advantage instead. However the traditional 3D graphics pipeline cannot take advantage of the smaller display because its run time depends mostly on the number of polygons to be rendered. In contrast, the run time of image-based rendering methods depends mainly on the display resolution. Therefore it is well suited for mobile devices. Furthermore, we may use the network connection to build a client-server framework, which allows us to integrate with nonimage-based rendering programs. We present our system framework and the experiment results on PocketPC® based devices in this work.
1331907
An efficient representation of complex materials for real-time rendering
In this paper, we propose an appearance representation for general complex materials which can be applied in real-time rendering framework. By combining a single parametric shading function (such as the Phong model) and the proposed spatial-varying residual function (SRF), this representation can recover the appearance of complex materials with little loss of visual fidelity. The difference between the real data and the parametric shading is directly fitted by a specific function for easy reconstruction. It is simple, flexible and easy to be implemented on programmable graphics hardware. Experiments show that the mean square error (MSE) between the reconstructed appearance and real photographs is less than 5%.
26211788
Mockup-driven fast-prototyping methodology for Web requirements engineering
Web application development differs from the development of traditional software in several significant ways; therefore requirements engineering for Web applications entails new demands accordingly. This paper proposes an extreme Web requirements engineering - mockup-driven fast-prototyping methodology to help elicit and finalize system requirements, as well as facilitate adjustment to quickly changing user requirements typical to Web applications. Supporting the inclusion of customer feedback early in the development process, this strategy minimizes the risk of wasting valuable development efforts because of ambiguous or incomplete specifications. Real-life experiences of the use of the methodology in industry are reported as examples.
14942562
Improving hallway navigation in mobile robots with sensor habituation
Habituation is a form of non-associative learning observed in a variety of species of animals. Arguably, it is the simplest form of learning. Nonetheless, the ability to habituate to certain stimuli implies plastic neural systems and adaptive behaviors. This article describes how computational models of habituation can be applied to real robots. In particular, we discuss the problem of the oscillatory movements observed when a Khepera robot navigates through narrow hallways. Results show that habituation to the proximity of the walls can lead to smoother navigation. Habituation to sensory stimulation to the sides of the robot does not interfere with the robot's ability to turn at dead ends and to avoid obstacles outside the hallway. This work shows that simple biological mechanisms of learning can be adapted to achieve better performance in real mobile robots.
32612296
Automating performance-related impact analysis through event based traceability
Current impact analysis techniques tend to focus on assessing the impact of change upon the system's functionality, whilst a consideration of performance related requirements is often deferred until after implementation. This tendency can lead to costly and time-consuming mistakes that frustrate customers and require frantic last-minute efforts to fix. This paper proposes a method for supporting performance-related impact analysis in a heterogeneous software engineering environment. An event-based approach is taken to establish dynamic traceability links, capable of propagating data values and commands between requirements and performance models. Quantitative values in performance related requirements are adjusted to reflect proposed changes, and impacted models are re-executed to measure the impact of the change. The resulting outputs are then automatically compared to relevant performance requirements and a system-wide report showing the impact of the proposed change upon performance is generated.
358297
LDI tree: a hierarchical representation for image-based rendering
Using multiple reference images in 3D image warping has been a challenging problem. Recently, the Layered Depth Image (LDI) was proposed by Shade et al. to merge multiple reference images under a single center of projection, while maintaining the simplicity of warping a single reference image. However it does not consider the issue of sampling rate. We present the LDI tree, which combines a hierarchical space partitioning scheme with the concept of the LDI. It preserves the sampling rates of the reference images by adaptively selecting an LDI in the LDI tree for each pixel. While rendering from the LDI tree, we only have to traverse the LDI tree to the levels that are comparable to the sampling rate of the output image. We also present a progressive refinement feature and a “gap filling” algorithm implemented by pre-filtering the LDI tree. We show that the amount of memory required has the same order of growth as the 2D reference images. This also bounds the complexity of rendering time to be less than directly rendering from all reference images. CR Categories: I.3.3 [Computer Graphics]: Picture/Image Generation Viewing Algorithms; I.3.6 [Computer Graphics] Methodology and Techniques Graphics data structures and data types; I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism. Additional
8773045
Characterizing and Exploiting Reference Locality in Data Stream Applications
In this paper, we investigate a new approach to process queries in data stream applications. We show that reference locality characteristics of data streams could be exploited in the design of superior and flexible data stream query processing techniques. We identify two different causes of reference locality: popularity over long time scales and temporal correlations over shorter time scales. An elegant mathematical model is shown to precisely quantify the degree of those sources of locality. Furthermore, we analyze the impact of locality-awareness on achievable performance gains over traditional algorithms on applications such asMAX-subset approximate sliding window join and approximate count estimation. In a comprehensive experimental study, we compare several existing algorithms against our locality-aware algorithms over a number of real datasets. The results validate the usefulness and efficiency of our approach.