7526155
BubbleUp: low latency fast-scan for media servers
Interactive multimedia applications require fast response time. Traditional disk scheduling schemes can incur high latencies, and caching data in memory to reduce latency is usually not feasible, especially if fast-scans need to be supported. In this study we propose a disk-based solution called BubbleUp. It significantly reduces the initial latency for new requests, as well as for fast-scan requests. The throughput of the scheme is comparable to that of traditional schemes, and it may even provide better throughput than mechanisms based on elevator disk scheduling. BubbleUp incurs a slight disk storage overhead, but we argue that through effective allocation, this cost can be minimized.
9408458
PBIR-MM: multimodal image retrieval and annotation
We demonstrate PBIR-MM, an integrated system that we have built for conducting multimodal image retrieval. The system combines the strengths of content-based soft annotation (CBSA), multimodal relevance feedback through active learning, and perceptual distance formulation and indexing. PBIR-MM supports multimodal query and annotation in any combination of its three basic modes: seed-by-nothing, seed-by-keywords, and seed-by-content. We demonstrate PBIR-MM on a couple of very large image sets provided by image vendors and crawled from the Internet.
19714040
Maximizing QoS for interactive DTV clients
In this study we present a client-based architecture that supports interactive DTV features (i.e. pause, replay and fast-forward) using the client's local disk and an Internet back-channel, together with the broadcast channels. Our study focuses on devising effective techniques for managing the client's local resources to maximize QoS. For individual video streams, we present an error concealment scheme that reconstructs video key frames suffering from channel errors. For the client as a whole, we propose a resource-scheduling policy that maximizes the client's QoS adaptively based on the viewer's preference under local resource constraints. We show that many interactive DTV applications can be supported under this client-based architecture more effectively than by the traditional server-based approaches.
10743717
Support vector machine active learning for image retrieval
Relevance feedback is often a critical component when designing image databases. With these databases it is difficult to specify queries directly and explicitly. Relevance feedback interactively determinines a user's desired output or query concept by asking the user whether certain proposed images are relevant or not. For a relevance feedback algorithm to be effective, it must grasp a user's query concept accurately and quickly, while also only asking the user to label a small number of images. We propose the use of a support vector machine active learning algorithm for conducting effective relevance feedback for image retrieval. The algorithm selects the most informative images to query a user and quickly learns a boundary that separates the images that satisfy the user's query concept from the rest of the dataset. Experimental results show that our algorithm achieves significantly higher search accuracy than traditional query refinement schemes after just three to four rounds of relevance feedback.
268452
Query planning with limited source capabilities
In information-integration systems, sources may have diverse and limited query capabilities. We show that because sources have restrictions on retrieving their information, sources not mentioned in a query can contribute to the query result by providing useful bindings. In some cases we can access sources repeatedly to retrieve bindings to answer a query, and query planning thus becomes considerably more challenging. We find all the obtainable answers to a query by translating the query and source descriptions to a simple recursive Datalog program, and evaluating the program on the source relations. This program often accesses sources that are not in the query. Some of these accesses are essential, as they provide bindings that let us query sources, which we could not do otherwise. However, some of these accesses can be proven not to add anything to the query's answer. We show in which cases these off-query accesses are useless, and prove that in these cases we can compute the complete answer to the query by using only the sources in the query. In the cases where off-query accesses are necessary, we propose an algorithm for finding all the useful sources for a query. We thus solve the optimization problem of eliminating the unnecessary source accesses, and optimize the program to answer the query.
18150673
The anatomy of a multimodal information filter
The proliferation of objectionable information on the Internet has reached a level of serious concern. To empower end-users with the choice of blocking undesirable and offensive websites, we propose a multimodal information filter, named MORF. In this paper, we present MORF's core components: its confidence-based classifier, a Cross-bagging ensemble scheme, and multimodal classification algorithm. Empirical studies and initial statistics collected from the MORF filters deployed at sites in the U.S. and Asia show that MORF is both efficient and effective, due to our classification methods.
9658544
Effect of Malicious Synchronization
We study the impact of malicious synchronization on computer systems that serve customers periodically. Systems supporting automatic periodic updates are common in web servers providing regular news update, sports scores or stock quotes. Our study focuses on the possibility of launching an effective low rate attack on the server to degrade performance measured in terms of longer processing time and request drops due to timeouts. The attackers are assumed to behave like normal users and send one request per update cycle. The only parameter utilized in the attack is the timing of the requests sent. By exploiting the periodic nature of the updates, a small number of attackers can herd users' update requests to a cluster and arrive in a short period of time. Herding can be used to discourage new users from joining the system and to modify the user arrival distribution, so that the subsequent burst attack will be effective. While the herding based attacks can be launched with a small amount of resource, they can be easily prevented by adding a small random component to the length of the update interval.
15998300
Shortest path amidst disc obstacles is computable
An open question in Exact Geometric Computation is whether there re transcendental computations that can be made "geometrically exact".Perhaps the simplest such problem in computational geometry is that of computing the shortest obstacle-avoiding path between two points p, q in the plane, where the obstacles re collection of n discs.This problem can be solved in O (n 2 log n)time in the Real RAM model, but nothing was known about its computability in the standard (Turing) model of computation. We first show the Turing-computability of this problem,provided the radii of the discs are rationally related. We make the usual assumption that the numerical input data are real algebraic numbers. By appealing to effective bounds from transcendental number theory, we further show single-exponential time upper bound when the input numbers are rational.Our result ppears to be the first example of non-algebraic combinatorial problem which is shown computable. It is also rare example of transcendental number theory yielding positive computational results.
6661888
A wavelet approach to foveating images
Motivated by applications of foveated images in visualization, we introduce the foveation transform of an image. We study the basic properties of these transforms using the multiresolution framework of Mallat. We also consider practical methods of realizing such transforms. In particular, we introduce a new method for foveating images based on wavelets. Preliminary experimental results are shown.
11249256
A unified framework for resolving ambiguity in copy detection
Copy detection is an important component of digital rights management and can be implemented using a retrieval-based approach. Under this approach, a query image, suspected to be a copy, is compared against all the images in the owner database. The comparison is done based on a distance metric in feature space. The performance of such a system depends on the mutual separation of the feature representation of the images in the database. In this paper we propose a framework that increases this mutual separation by literally shifting them away from each other. The idea of modifying the features derives its inspiration from the field of watermarking. It is also important to make sure that the semantics of the images do not change after modification. Thus the focus of this paper is on how to modify the images in the database, so that the mutual separation between the images in feature space is above a certain threshold and the distortion induced is minimized. This problem can be formulated as a non-convex optimization problem which is difficult to solve. We propose a restriction of the problem and solve it using second-order cone programming. We present a practical implementation of our framework, named RAM, which uses AFMT as the feature representation. We conduct experiments to test the performance of RAM.
14264886
Geometric properties of watermarking schemes
A variety of image watermarking schemes have been proposed using orthogonal transformations, projections, and coding techniques to embed imperceptible watermarks into images. Analytical studies of the watermarking problem have typically been based on studying the performance limits of these known algorithms. In contrast, this paper formalizes the watermarking problem in an "algorithm independent" framework, representing any watermarking algorithm as a partition of the image space into a collection of sets, and defining requirements of these sets that must be met by any solution to the watermarking problem. Specifically, these requirements define and constrain the false-alarm ratio, distortion, robustness and security of a watermarking system. Using this formalism, we first characterize common features of algorithms that solve the watermarking problem. We show how the requirements defined earlier force important differences between watermarking signal sets and classical communication systems signal sets. Next, we show how common components of existing watermarking algorithms (e.g. transformations, projections, and coding) can be associated with specific requirements of the watermarking definition. Finally, we show how our new formalism of the watermarking problem provides a procedure for optimal design of watermarking systems to target specified false-alarm, distortion, and robustness objectives.