We present a newly developed algorithm for automatically segmenting videos into basic shot units. A basic shot unit can be understood as an unbroken sequence of frames taken from one camera. At first we calculate the frame difference by using the local histogram comparison, and then we dynamically scale the frame difference by Log-formula to compress and enhance the frame difference. Finally we...

This paper explores the problem of identifying sentence boundaries in the transcriptions produced by automatic speech recognition systems. An experiment which determines the level of human performance for this task is described as well as a memorybased computational approach to the problem. 1 T h e P r o b l e m This paper addresses the problem of identifying sentence boundaries in the transcri...

This paper describes the application of Bayesian networks to the generation of explanations for the evidence provided by one or more 1-D profiles. Experiments with synthetic images and Cephalograms are described.

We propose and motivate a novel task: paragraph segmentation. We discuss and compare this task with text segmentation and discourse parsing. We present a system that performs the task with high accuracy. A variety of features is proposed and examined in detail. The best models turn out to include lexical, coherence, and structural features.

Digital images are often corrupted by different noises. These noises can be removed by designing an efficient filter. Based upon the specified operation the pixels are classified. Absolute Difference Based Progressive Switching Median Filter (ADBPSMF) outperforms all other filter for the removal of impulse noise from corrupted images. This filter performs two basic operations for efficient nois...

The detection of novel or abnormal input vectors is of importance in many monitoring tasks, such as fault detection in complex systems and detection of abnormal patterns in medical diagnostics. We have developed a robust method for novelty detection, which aims to minimize the number of heuristically chosen thresholds in the novelty decision process. We achieve this by growing a gaussian mixtur...

Event boundary detection is in and of itself a useful application in wireless sensor networks (WSNs). Typically, it includes the detection of a large-scale spatial phenomenon such as the transportation front line of a contamination or the diagnosis of network health. In this paper, we present FEBD, a fully distributed and light-weight Fault-tolerant Event Boundary Detection scheme. FEBD feature...

Even with the advent of more sophisticated, data-hungry methods, boosted decision trees remain extraordinarily successful for fast rigid object detection, achieving top accuracy on numerous datasets. While effective, most boosted detectors use decision trees with orthogonal (single feature) splits, and the topology of the resulting decision boundary may not be well matched to the natural topolo...

Boundary detection in natural images is a fundamental problem in many computer vision tasks. In this paper, we argue that early stages in primary visual cortex provide ample information to address the boundary detection problem. In other words, global visual primitives such as object and region boundaries can be extracted using local features captured by the receptive fields. The anatomy of vis...