2546960
The Source Coding Game With a Cheating Switcher
The problem of finding the rate-distortion function of an arbitrarily varying source (AVS) composed of a finite number of memoryless subsources is revisited. Berger's 1971 paper “The Source Coding Game” solves this problem when the adversary is allowed only strictly causal access to the subsource realizations. The case when the adversary has access to the subsource realizations non-causally is considered. This new rate-distortion function is determined to be the maximum of the rate-distortion function over a set of independent and identically distributed (IID) random variables that can be simulated by the adversary. The results are extended to allow for partial or noisy observations of subsource realizations. The model is further explored by attempting to find the rate-distortion function when the `adversary' is actually helpful. Finally, a bound is developed on the uniform continuity of the IID rate-distortion function for finite-alphabet sources. The bound is used to give a sufficient number of distributions that need to be sampled to compute the rate-distortion function of an AVS to within a desired accuracy. The bound is also used to give a rate of convergence for the estimate of the rate-distortion function for an unknown IID source.
3263120
The price of ignorance: The impact of side-information on delay for lossless source-coding
Inspired by the context of compressing encrypted sources, this paper considers the general tradeoff between rate, end-to-end delay, and probability of error for lossless sou rce coding with side-information. The notion of end-to-end delay is made precise by considering a sequential setting in which source symbols are revealed in real time and need to be reconstructed at the decoder within a certain fixed latency requirement. Upper bounds are derived on the reliability functions with delay when side-informatio n is known only to the decoder as well as when it is also known at the encoder. When the encoder is not ignorant of the side-information (including the trivial case when there is no sideinformation), it is possible to have substantially better t radeoffs between delay and probability of error at all rates . This shows that there is a fundamental price of ignorance in terms of end-to-end delay when the encoder is not aware of the side information. This effect is not visible if o nly fixed-block-length codes are considered. In this way, side-information in source-coding plays a role analogous t o that of feedback in channel coding. While the theorems in this paper are asymptotic in terms of long delays and low probabilities of error, an example is used to show that the qualitative effects describ ed here are significant even at short and moderate delays.
9272685
Genetic algorithm for affine point pattern matching
Point pattern matching (PPM) is an important topic in the fields of computer vision and pattern recognition. According to if there exists a one to one mapping between the two point sets to be matched, PPM can be divided into the case of complete matching and the case of incomplete matching. According to if utilizing information other than 2-D image coordinates, PPM can be divided into labelled point-matching case and unlabelled point-matching case. Using partial Hausdorff distance, this paper presents a genetic algorithm (GA) based method to solve the incomplete unlabelled matching problem under general affine transformation. Since it successfully reduces the solution space of GA by constructing 'feature ellipses' of point sets, the method can achieve high computing efficiency and good matching results. Theoretical analysis and simulation results show that the new algorithm is very effective.
12575767
Universal Quadratic Lower Bounds on Source Coding Error Exponents
We consider the problem of block-size selection to achieve a desired probability of error for universal source coding. While Baron, et al. (2004; 1973) studied this question for rates in the vicinity of entropy for known distributions using central-limit-theorem techniques, we are interested in all rates for unknown distributions and use error-exponent techniques. By adapting a technique of Gallager from the exercises of Gallager (1971), we derive a universal lower bound to the source-coding error exponent that depends only on the alphabet size and is quadratic in the gap to entropy.
16124776
Interference channel capacity region for randomized fixed-composition codes
The randomized fixed-composition codes with optimal decoding error exponents are recently studied in [11], [12] for the finite alphabet interference channel with two transmitter-receiver pairs. In this paper we investigate the capacity region for randomized fixed-composition codes. A complete characterization of the capacity region of the said coding scheme is given. The inner bound is derived by showing the existence of a positive error exponent within the capacity region. A simple universal decoding rule is given. The tight outer bound is derived by extending a technique first developed in [10] for single input output channels to interference channels. It is shown that even with a sophisticated time-sharing scheme among randomized fixed-composition codes, the capacity region of the randomized fixed-composition coding is not bigger than the known Han-Kobayashi [24] capacity region. This suggests that the study of the average behavior of randomized codes are not sufficient in finding new capacity regions.
27390874
Color Sectors and Edge Features for Content-Based Image Retrieval
We provide a new image retrieval model which integrates the spatial distributing information of colors and the shape features. The color features are represented by an amelioration of HSV color model: color sector. To describe the relative position and orientation of objects within the image, hue edges in the image, computed using Canny approach, are processed by Hough transform to generate the spatial histogram which is used as shape representation. To address matching of image, we define two global distance measures based on the accumulative distance and vector-based distance to compare the similarity of two images. Experimental results indicate that our approach provides higher retrieval rate than that of single feature (color), is a better tradeoff between high efficiency and reasonable precision.
44378446
Component-Oriented Digital Signal Processors
18226410
Real-time tracking with multiple cues by set theoretic random search
Conventional treatment of visual tracking has been to optimize an objective function in a probabilistic framework. In this formulation, efficient algorithms employing simple prior distributions are usually insufficient to handle clutters (e.g., Kalman filter). On the other hand, distributions that are complex enough to incorporate all a priori knowledge can make the problem computationally intractable (e.g., particle filters (PF)). This paper proposes a new formulation of visual tracking where every piece of information, be it from a priori knowledge or observed data, is represented by a set in the solution space and the intersection of these sets, the feasibility set, represents all acceptable solutions. Based on this formulation, we propose an algorithm whose objective is to find a solution in the feasibility set. We show that this set theoretic tracking algorithm performs effective face tracking and is computationally more efficient than standard PF-based tracking.
16280666
Component-oriented radars with probabilistic timing guarantees
In recent years, many modern phased-array radars are built with commercial off-the-shelf components, and the functions of many hardware components are also reimplemented by software modules. In such systems, radar tasks could be modeled as distributed real-time tasks which require end-to-end deadline guarantees and have precedence constraints. Different from most previous work on either algorithms with restrictions in resource utilization or heuristics without analytical ways for schedulability guarantees, the objective of this paper is to propose a joint real-time scheduling algorithm for both transmitter/receiver and signal processor workloads with an analytical framework for offline probabilistic analysis and online admission control. The strength of our approach is verified by analysis results and a series of experiments based on a real phased-array radar for air defense frigates
1776041
The design of distributed real-time video analytic system
Video has become an indispensable carrier of information and requires extremely computation expensive analysis to understand high level semantics. The computational difficulties in extracting embedded information and bridging the semantic gap present the major challenges in interoperability, scalability and real-time response of video analytic systems. In this paper, we propose a distributed scalable infrastructure VAP (Video Analytic Platform) for supporting real-time video stream analysis. In VAP, the application requirements are represented as a Directed Acrylic Graph (DAG), where nodes stand for video analysis computation modules and links show data flow and dependencies between nodes. VAP leverages UIMA (Unstructured Information Management Architecture) framework as the data flow control engine and multiple commodity databases as the storage and computation resources. The actual executions of video analysis computation modules have been pushed down into database engines to minimize the data movement cost. We initially choose video surveillance in retail store as a representative application domain. As a case study, a prototype system has been developed to achieve fundamental functions of real-time video surveillance, including video capture/store, human detection/tracking and customer shopping trajectory analysis.