31922506
Layering-based color filter array interpolation
This paper presents a new method to interpolate the color filter array (CFA) pattern that is commonly used in a single-sensor digital camera. The proposed method involves two main steps: slicing the color planes into layers to identify smooth local image regions; estimating the missing color values based on the spectral correlation between color planes. The performance of the proposed algorithm is evaluated by comparing the results with those generated by other existing methods. It shows that the proposed method outperforms other methods in terms of both subjective and objective image quality.
147466
A vision-based approach to early detection of drowning incidents in swimming pools
We present in this paper a vision-based approach to detection of drowning incidents in swimming pools at the earliest possible stage. The proposed approach consists of two main parts: a vision component which can reliably detect and track swimmers in spite of large scene variations of monitored pool areas, and an event-inference module which parses observation sequences of swimmer features for possible drowning behavioral signs. The vision component employs a model-based approach to represent and differentiate the background pool areas and foreground swimmers. The event-inference module is constructed based on a finite state machine, which integrates several reasoning rules formulated from universal motion characteristics of drowning swimmers. Possible drowning incidents are quickly detected using a sequential change detection algorithm. We have applied the proposed approach to a number of video clips of simulated drowning and obtained promising results as reported in this paper.
5556167
A color histogram based people tracking system
A system using color histogram based recognition technique is presented for tracking of moving people. The proposed system aims to resolve the identity of each tracked person after an occlusion, which is a common problem encountered in tracking of multiple objects. The system recognizes and keeps track of moving people with the aid of their color histograms. To make the recognition more robust against change of background illumination, a shadow-removal scheme is designed to select only those pixels belonging to the tracked people for constructing their color histograms. Experimental results of real video data are reported to show the efficacy of the proposed system.
27936359
A new content-based hybrid video transcoding method
Many video transcoding architectures have been proposed to reduce the bitrates of compressed video bitstreams. Requantization of transformed coefficients (such as DCT coefficients), spatial resolution down-sampling, and temporal resolution down-sampling are the three transcoding tools which are commonly used to reduce compressed video bitrates. We propose a new video transcoding method that combines the use of different transcoding tools to transcode compressed video bit streams to various target bitrates while maintaining good subjective/objective video quality. The transcoding tools are selected based on the video content, which is characterized by two video content descriptors inferring the video spatial and motion activities, respectively. These two content descriptors can be readily computed from the compressed video bit streams without full decompression. Experimental results show that the proposed method can provide better video quality than other existing transcoders that make use of a single transcoding tool.
33005423
Unsupervised clustering of dominant scenes in sports video
We propose a new and efficient approach for clustering dominant scenes in sports video. To perform clustering in an unsupervised manner, we devise a recursive peer-group filtering (PGF) scheme to identify prototypical shots for each dominant scene, and examine time coverage of these prototypical shots to decide the number of dominant scenes for each sports video under analysis. To improve clustering efficiency, we employ principal component analysis and linear discriminant analysis to project high dimensional shot features to lower dimensional spaces suitable for classification. The main contribution of the paper lies in the formulation of clustering dominant scenes in sports video and the development of an efficient, unsupervised solution making use of PGF, time-coverage criterion, and subspace analysis. Experimental results obtained from various types of sports videos are presented to show the efficacy of the proposed approach.
34798576
Video transcoding for fast forward/reverse video playback
Fast forward and fast reverse playbacks are two common video browsing functions provided in many analog and digital video players. They help users quickly find and access video segments of interest by scanning through the content of a video at a faster than normal playback speed. We propose a video transcoding approach to realizing fast forward and reverse video playbacks by generating a new compressed video from a pre-coded video. To reduce the computational requirements, we design and compare several fast algorithms for estimating the motion vectors required in transcoded video. To accommodate changes due to frame skipping for fast video playback, we also alter the group-of-pictures structure of transcoded video. In addition, subjective tests are conducted to assess the minimum video peak-signal-to-noise-ratio degradation that is perceptible to viewers at different fast playback speeds. To this end, we obtain an adaptive video transcoding method, which combines intra-coding and inter-coding with a fast motion vector reestimation method to strike a good balance between computational complexity and transcoded video quality. Experimental results are reported to show the efficacy of the proposed method.
20191236
Optimal Rebating Strategies in Peer-to-Peer Content Distribution
Developed the algorithms that were the firm's core Intellectual Property (IP) at founding.
14371676
On the Formation of Peer-to-Peer Networks: Self-Organized Sharing and Groups
In this paper, we investigate the formation of peer-to-peer (P2P) networks with rational participating agents (active peers). In the absence of a central planner, peers choose their own utility-maximizing strategies for coalition and peer formation. P2P networks evolve dynamically through the activities of interactions among individual nodes and group units. We propose a framework for multilevel formation dynamics, including an individual level (content sharing decision and group selection) and a group level (membership admission). The respective utilities of the individual node and the collective player are formulated as functions of operational performance metrics such as expected content availability, search delay, transmission delay, and download delay. We study the impacts of various system parameters on the emergence of self-organized P2P network configuration features such as free-riding level and group size. Furthermore, we investigate the stability and efficiency of P2P networks and propose internal transfer mechanisms that force stable networks to become efficient.
10154529
Comparing uniform and flexible policies for software maintenance and replacement
The importance of software maintenance in managing the life-cycle costs of a system cannot be overemphasized. Beyond a point, however, it is better to replace a system rather than maintain it. We derive model and operating policy that reduces the sum of maintenance and replacement costs in the useful life of a software system. The main goal is to compare uniform (occurring at fixed time intervals) versus flexible (occurring at varying, planned time intervals) polices for maintenance and replacement. The model draws from the empirical works of earlier researchers to consider 1) inclusion of user requests for maintenance, 2) scale economies in software maintenance, 3) efficiencies derived from replacing old software technology with new software technology, and 4) the impact of software reuse on replacement and maintenance. Results from our model show that the traditional practice of maintaining or replacing a software system at uniform time intervals may not be optimal. We also find that an increase in software reuse leads to more frequent replacement, but the number of maintenance activities is not significantly impacted.
14496219
Optimal Processing Policies for an e-Commerce Web Server
The explosive growth in online shopping has provided online retailers impressive opportunities to extend revenue and profit. However, retailers may lose considerable online business from slow response times at electronic shopping sites. Although increasing server capacity may improve response time, the resources needed to do so are clearly not free. In this study, we propose a scheme that can improve a server's performance with no more than its current capacity. This scheme is based on priority processing, where the priority assigned to a customer depends on the potential revenue that is likely to be generated from the customer. The results for single-period analysis show that the benefit from priority processing increases as the server becomes more heavily utilized. 
 
We have also modeled a multiperiod version of the problem, where the demand in a period depends on the quality of service (QoS) that buyers receive in the previous period. In the multiperiod problem, both the server capacity and the processing policy in each period are determined optimally. Here, it may be optimal for the retailer to sacrifice profit and increase QoS in initial periods in order to increase demand (and revenue) in later periods. Thus, the processing policy of the server evolves from an emphasis on QoS in initial periods, to one on profit in subsequent periods.
181942
Search engine driven author disambiguation
In scholarly digital libraries, author disambiguation is an important task that attributes a scholarly work with specific authors. This is critical when individuals share the same name. We present an approach to this task that analyzes the results of automatically-crafted Web searches. A key observation is that pages from rare Web sites are stronger source of evidence than pages from common Web sites, which we model as inverse host frequency (IHF). Our system is able to achieve an average accuracy of 0.836