Fast similarity search and clustering of video sequences on the world-wide-web

We define similar video content as video sequences with almost identical content but possibly compressed at different qualities, reformatted to different sizes and frame-rates, undergone minor editing in either spatial or temporal domain, or summarized into keyframe sequences. Building a search engine to identify such similar content in the World-Wide Web requires: 1) robust video similarity measurements; 2) fast similarity search techniques on large databases; and 3) intuitive organization of search results. In a previous paper, we proposed a randomized technique called the video signature (ViSig) method for video similarity measurement. In this paper, we focus on the remaining two issues by proposing a feature extraction scheme for fast similarity search, and a clustering algorithm for identification of similar clusters. Similar to many other content-based methods, the ViSig method uses high-dimensional feature vectors to represent video. To warrant a fast response time for similarity searches on high dimensional vectors, we propose a novel nonlinear feature extraction scheme on arbitrary metric spaces that combines the triangle inequality with the classical Principal Component Analysis (PCA). We show experimentally that the proposed technique outperforms PCA, Fastmap, Triangle-Inequality Pruning, and Haar wavelet on signature data. To further improve retrieval performance, and provide better organization of similarity search results, we introduce a new graph-theoretical clustering algorithm on large databases of signatures. This algorithm treats all signatures as an abstract threshold graph, where the distance threshold is determined based on local data statistics. Similar clusters are then identified as highly connected regions in the graph. By measuring the retrieval performance against a ground-truth set, we show that our proposed algorithm outperforms simple thresholding, single-link and complete-link hierarchical clustering techniques.     

Multiple sender distributed video streaming

With the explosive growth of video applications over the Internet, many approaches have been proposed to stream video effectively over packet switched, best-effort networks. We propose a receiver-driven protocol for simultaneous video streaming from multiple senders to a single receiver in order to achieve higher throughput, and to increase tolerance to packet loss and delay due to network congestion. Our receiver-driven protocol employs a novel rate allocation algorithm (RAA) and a packet partition algorithm (PPA). The RAA, run at the receiver, determines the sending rate for each sender by taking into account available network bandwidth, channel characteristics, and a prespecified, fixed level of forward error correction, in such a way as to minimize the probability of packet loss. The PPA, run at the senders based on a set of parameters estimated by the receiver, ensures that every packet is sent by one and only one sender, and at the same time, minimizes the startup delay. Using both simulations and Internet experiments, we demonstrate the effectiveness of our protocol in reducing packet loss.     

Lossless Compression Algorithms for Hierarchical IC Layout

An important step in today's integrated circuit (IC) manufacturing is optical proximity correction (OPC). While OPC increases the fidelity of pattern transfer to the wafer, it also significantly increases IC layout file size. This has the undesirable side effect of increasing storage, processing, and I.O. times for subsequent steps of mask preparation. In this paper, we propose two techniques for compressing layout data, including OPC layout, while remaining compliant with existing industry standard formats such as OASIS and GDSII. Our approach is to eliminate redundancies in the representation of the geometrical data by finding repeating groups of geometries between multiple cells and within a cell. We refer to the former as ldquointercell subcell detection (InterSCD)rdquo and the latter as ldquointracell subcell detection (IntraSCD).rdquo We show both problems to be nondeterministic polynomial time hard (NP-hard), and propose two sets of heuristics to solve them. For OPC layout data, we also propose a fast compression method based on IntraSCD which utilizes the hierarchical information in the pre-OPC layout data. We show that the IntraSCD approach can also be effective in reconstructing hierarchy from flattened layout data. We demonstrate the results of our proposed algorithms on actual IC layouts for 90-nm, 130-nm, and 180-nm feature size circuit designs.     

New properties of sigma-delta modulators with DC inputs

New properties of single- and double-loop sigma-delta modulators with constant inputs are derived by exploiting the inherent structure os the output sequences or codewords that the modulators are capable of producing. Upper bounds are derived on the number of N-bit codewords for the single- and double-loop modulators. Analytical lower bounds on the mean squared error (MSE) obtainable by any decoder, linear or nonlinear, in approximating the constant input are also derived. Optimal nonlinear decoders for constant inputs based on a table lookup approach which operates directly on the nonuniform quantization intervals are considered. Using simulations is is found that the optimal nonlinear decoders perform better than linear decoders, by about 3 and 20 dB for the single- and double-loop modulators, respectively. A cascade structure specifically for constant inputs is introduced, and its corresponding decoding algorithm is derived. It is shown that for a fixed latency, the MSE performance of the cascade structure is 12 dB superior, and its throughput is twice that of the conventional two-stage MASH modulator     

Reconstruction of two-dimensional signals from level crossings

Recent results indicate that reconstruction of two-dimensional signals from crossings of one level requires, in theory and practice, extreme accuracy in positions of the samples. The representation of signals with one-level crossings can be viewed as a tradeoff between bandwidth and dynamic range, in the sense that if the available bandwidth is sufficient to preserve the level crossings accurately, then the dynamic range requirements are significantly reduced. On the other hand, representation of signals by their samples at the Nyquist rate can be considered as requiring relatively small bandwidth and large dynamic range, because, at least in theory, amplitude information at prespecified points is needed, to infinite precision. An overview of existing results in zero crossing representation is presented, and a number of new results on sampling schemes for reconstruction from multiple-level threshold crossing are developed. The quantization characteristics of these sampling schemes appear to lie between those of Nyquist sampling and one-level crossing representations, thus bridging the gap between explicit Nyquist sampling and implicit one-level crossing sampling strategies     

Edge-based 3-D camera motion estimation with application to videocoding

Two classes of algorithms for modeling camera motion in video sequences captured by a camera are proposed. The first class can be applied when there is no camera translation and the motion of the camera can be adequately modeled by zoom, pan, and rotation parameters. The second class is more general in that it can be applied when the camera is undergoing a translation motion, as well as a rotation and zoom and pan. This class uses seven parameters to describe the motion of the camera and requires the depth map to be known at the receiver. The salient feature of both algorithms is that the camera motion is estimated using binary matching of the edges in successive frames. The rate distortion characteristics of the algorithms are compared with that of the block matching algorithm and show that the former provide performance characteristics similar to those of the latter with reduced computational complexity.     

A new class of B/W halftoning algorithms

A new class of dithering algorithms for black and white (B/W) images is presented. The basic idea behind the technique is to divide the image into small blocks and minimize the distortion between the original continuous-tone image and its low-pass-filtered halftone. This corresponds to a quadratic programming problem with linear constraints, which is solved via standard optimization techniques. Examples of B/W halftone images obtained by this technique are compared to halftones obtained via existing dithering algorithms.