14075719
Receiver-based rate-distortion optimized interactive streaming for scalable bitstreams of light fields
The paper proposes a receiver-based rate-distortion optimized framework to stream interactively scalable bitstreams of light fields. Based on the desired viewpoints, the predicted future buffer state, the network characteristics, and the target transmission rate, the receiver customizes the data request in order to minimize the distortion in the frames to be rendered. Experimental results show that the proposed framework improves the rendering quality by 1.0-2.8 dB over a heuristic scheme at the same rate. Correspondingly, to achieve the same rendering quality the proposed framework reduces 25-35% of the rate over the heuristic scheme.
15632441
Direction-Adaptive Discrete Wavelet Transform via Directional Lifting and Bandeletization
We propose an adaptive lifted discrete wavelet transform to locally adapt the filtering direction to the geometric flow in the image. The proposed approach refines previous directional lifting approaches to achieve superior compression performance with less demand for computation. Additionally, a bandeletization procedure is combined with directional lifting in a unified framework to further remove the correlation in the wavelet coefficients. Up to 2.8 dB improvement in PSNR over the conventional 2-D CDF 9/7 wavelet transform for natural images is reported. Significant improvement in subjective quality is also observed.
1786671
Light field compression using disparity-compensated lifting and shape adaptation
We propose disparity-compensated lifting for wavelet compression of light fields. With this approach, we obtain the benefits of wavelet coding, such as scalability in all dimensions, as well as superior compression performance. Additionally, the proposed approach solves the irreversibility limitations of previous light field wavelet coding approaches, using the lifting structure. Our scheme incorporates disparity compensation into the lifting structure for the transform across the views in the light field data set. Another transform is performed to exploit the coherence among neighboring pixels, followed by a modified SPIHT coder and rate-distortion optimized bitstream assembly. A view-sequencing algorithm is developed to organize the views for encoding. For light fields of an object, we propose to use shape adaptation to improve the compression efficiency and visual quality of the images. The necessary shape information is efficiently coded based on prediction from the existing geometry model. Experimental results show that the proposed scheme exhibits superior compression performance over existing light field compression techniques.
2500932
Mediating electronic meetings
Electronic meeting control has been the focus of many research efforts; however, extensively adopted standards are still unavailable. In this paper, we present a generic model for electronic meeting control. Our model is based on the formal meeting protocol commonly known as the parliamentary procedure or Robert's Rules of Order (RRO). Capturing the essential features of traditional RRO, we suggest extension mechanisms in order to exploit the capabilities of electronic media. Centered on the concept of a discussion thread, our extended RRO model can handle concurrent meeting activities, multiple floors, amendment nesting, and discussion hierarchies. M-Net, an electronic meeting system, is introduced as an example supported by our model.
11602397
Compiling process algebraic specifications into timed automata
The authors present LTP (Language of Timed Processes), a process-algebra-based specification language, for the specification of real-time applications. In addition to timing requirements involving the execution time of individual computations, LTP can specify timing constraints that are associated with process descriptions: periodic constraints and sporadic constraints. Periodic processes (e.g. sensors) are usually time-driven; sporadic processes are usually event-driven. In LTP common real-time constraints such as delays, deadlines, and timeouts can be modeled conveniently. They specifically introduce a new construct for modeling periodic behavior, which is quite common in real-time applications. They validate LTP specifications by translating from LTP to a kind of timed automata that is amenable to well-known model checking techniques. Although the models of LTP specifications, commonly known as timed transition systems, are usually infinite because of the presence of time, the translation results in a finite representation by which automatic verification is possible.
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
18983514
Sequence Learning in Mobile Robots Using Avalanche Neural Networks
This paper describes the implementation of a neural network for sequence learning that is based on a neurocomputational theory of learning. The network is implemented on a physical mobile robot in order to learn to reproduce sequences of motor actions. At the onset of a conditioned stimulus the robot is presented with a sequence of visual stimuli that produce reactive motor actions of different duration. Initial results show that after learning the robot can approximate the motor sequence with no visual stimulation.
5203884
Reconfigurable Web Wrapper Agents for Web Information Integration
This paper provides a solution for rapidly building software agents that can serve as Web wrappers for biological information integration. We define an XML-based language called WNDL, which provides a representation of a Web browsing session. A WNDL script describes how to locate the data, extract the data and combine the data. By executing different WNDL scripts, user can automate virtually all types of Web browsing sessions. We also describe IEPAD, a data extractor based on pattern discovery techniques. IEPAD allows our software agents to automatically discover the extraction rules to extract the contents of a structurally formatted Web page without the need to label a Web page to train a wrapper. With a programmingby-example authoring tool, a user can generate a complete Web wrapper agent by browsing the target Web sites. We have built a variety of applications to demonstrate the feasibility of our approach.