5431799
Automating the creation of a digital video library
52819119
Video skimming and characterization through the combination of image and language understanding
Digital video is rapidly becoming important for education, entertainment and a host of multimedia applications. With the size of the video collections growing to thousands of hours, technology is needed to effectively browse segments in a short time without losing the content of the video. We propose a method to extract the significant audio and video information and create a skim video which represents a very short synopsis of the original. The goal of this work is to show the utility of integrating language and image understanding techniques for video skimming by extraction of significant information, such as specific objects, audio keywords and relevant video structure. The resulting skim video is much shorter; where compaction is as high as 20:1, and yet retains the essential content of the original segment. We have conducted a user-study to test the content summarization and effectiveness of the skim as a browsing tool.
5238518
Evolving video skims into useful multimedia abstractions
This paper reports two studies that measured the effects of different “video skim” techniques on comprehension, navigation, and user satisfaction. Video skims are compact, content-rich abstractions of longer videos, condensations that preserve frame rate while greatly reducing viewing time. Their characteristics depend on the image- and audio-processing techniques used to create them. Results from the initial study helped refine video skims, which were then reassessed in the second experiment. Significant benefits were found for skims built from audio sequences meeting certain criteria.
14666057
Video skimming and characterization through the combination of image and language understanding techniques
Digital video is rapidly becoming important for education, entertainment, and a host of multimedia applications. With the size of the video collections growing to thousands of hours, technology is needed to effectively browse segments in a short time without losing the content of the video. We propose a method to extract the significant audio and video information and create a "skim" video which represents a very short synopsis of the original. The goal of this work is to show the utility of integrating language and image understanding techniques for video skimming by extraction of significant information, such as specific objects, audio keywords and relevant video structure. The resulting skim video is much shorter, where compaction is as high as 20:1, and yet retains the essential content of the original segment.
45488813
Parallel application performance on shared high performance reconfigurable computing resources
The use of a network of shared, heterogeneous workstations each harboring a reconfigurable computing (RC) system offers high performance users an inexpensive platform for a wide range of computationally demanding problems. However, effectively using the full potential of these systems can be challenging without the knowledge of the system's performance characteristics. While some performance models exist for shared, heterogeneous workstations, none thus far account for the addition of RC systems. Our analytic performance model includes the effects of the reconfigurable device, application load imbalance, background user load, basic message passing communication, and processor heterogeneity. The methodology proves to be accurate in characterizing these effects for applications running on shared, homogeneous, and heterogeneous HPRC resources. The model error in all cases was found to be less than 5% for application runtimes greater than 30s, and less than 15% for runtimes less than 30s.
26831752
Incrementally visualising criminal networks
Understanding the information gathered thus far in a criminal investigation is of great importance, particularly in terms of guiding its future course. Since the late 1980's the use of software tools to provide visualisations of this information has become increasingly common. The objective of such tools is to provide, in a readily comprehensible way, the social network of all the people involved. This may include the victims, suspects, witnesses, acquaintances and locations of interest in the investigation such as workplaces or nightclubs. Such diagrammatic representations often provide the focus for discussion among the investigating team and are incrementally added to as new facts are discovered. In this paper we present a brief overview of this important subject area and discuss how such software products could be further enhanced. We also present an example that illustrates the basic principles using a demonstrator we developed.
835724
Database Support for Exploring Criminal Networks
An established method of comprehending the data gathered thus far in a criminal investigation is to incrementally visualize it as a network, such as in the diagram displayed below which is referred to as a link chart, to ascertain if, and how, objects of interest are connected.
7156330
Balancing FPGA Resource Utilities
Balancing the use of FGPA resources such as FPGA slices, block RAMs, and block multipliers is desirable in many FPGA applications. This task can be carried out manually by experienced hardware designers with the use of hardware description languages, such as Verilog and VHDL. However, many users of reconfigurable computers are software developers who depend on hardware synthesis tools or even high-level synthesis tools to deal with the details beneath the application logic. In this paper, a motivating example of balancing FPGA resource utilities is given first. A module selection optimization problem is then formulated, in which, balancing FPGA resource utilities is treated as a constraint, so that the solution to the module selection problem is the balanced use of the FPGA resources. Several variations of the problem formulation are discussed. A naive algorithm and an efficient greedy algorithm to solve the problem are provided and compared. Some experimental results are also presented.
14206506
The role of diverse populations in phylogenetic analysis
The most popular approaches for reconstructing phylogenetic trees attempt to solve NP-hard optimization criteria such as maximum parsimony (MP). Currently, the best-performing heuristic for reconstructing MP trees is Recursive-Iterative DCM3 (Rec-I-DCM3), which uses a single tree (or solution) to guide its way through an exponentially-sized tree space. To improve performance further, we designed Cooperative Rec-I-DCM3, a population-based approach for utilizing a population of Rec-I-DCM3 trees.We compare the performance of Cooperative Rec-I-DCM3 to Rec-I-DCM3 on four large biological datasets. Of particular interest is Cooperative Rec-I-DCM3's selection criteria for maintaining a population of solutions. Our experiments reveal that diverse populations outperform Rec-I-DCM3 in terms of average rates of convergence to best-known MP scores. To achieve greater performance, we designed an elitist population strategy, in which each solution's tree score matches that of the best score found in each generation. The elitist strategy was by far the worst overall performer in our experiments. Hence, being greedy is not always the best approach. Instead, a population of diverse solutions allows our cooperative algorithm to achieve the greatest performance improvements.