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Video segmentation is a key step for the long videos recorded from Television channels to be represented in the hierarchical structure. In this paper, a novel approach based on acoustic cues for automatic segmenting television stream into individual programs is proposed. This presented method is composed of the following steps: Several sets of repetitions in the audio track is detected by using silence...
Current telepresence systems, while being a great step forward in videoconferencing, still have important points to improve in what eye-contact, gaze and gesture awareness concerns. Many-to-many communications are going to greatly benefit from mature auto-stereoscopic 3D technology; allowing people to engage more natural remote meetings, with proper eye-contact and better spatiality feeling. For this...
Pedestrian detection is one of the most popular research areas in video processing and it is vital for video surveillance systems. In this paper, we present a real-time pedestrian detection system based on Dalal and Triggs's human detection framework with the use of image segmentation and virtual mask. Image segmentation enables the system to focus only on the region of interest whereas the virtual...
This paper analyzes the basic method of digital video image processing, studies the vehicle license plate recognition system based on image processing in intelligent transport system, presents a character recognition approach based on neural network perceptron to solve the vehicle license plate recognition in real-time traffic flow. Experimental results show that the approach can achieve better positioning...
Digital video segmentation is an active area of research. Generally, the significances of this segmentation mask can be explained as follows: Firstly, the mask can be used for image examining, editing, compression, analysis and understanding. Secondly, the virtual reality system can use the panorama and mask to appear the virtual 3-D environment. So the research of such an efficient video segmentation...
Action recognition is a challenging problem in video analytics due to event complexity, variations in imaging conditions, and intra- and inter-individual action-variability. Central to these challenges is the way one models actions in video, i.e., action representation. In this paper, an action is viewed as a temporal sequence of local shape-deformations of centroid-centered object silhouettes, i...
In order to improve the accuracy of vehicle detection, and to solve the gradually changing brightness of light in the background and the movement of the objects in the background, this paper presents an algorithm that fast adapts to the background generation and updating. Focus on the objects with similar gray background, and moving object missing caused easily by segmentation, the threshold segmentation...
Stylized rendering, usually referred as non-photorealistic rendering, aims to reproduce artistic techniques in renderings, trying to express feelings and moods on the rendered scenes, as opposed to realistic rendering techniques, that aim to produce realistic renderings of artificial scenes. In this paper, we present a stylized rendering technique that aims to create synthetic sand-filled bottles,...
Cell segmentation is a challenging problem due to both the complex nature of the cells and the uncertainty present in video microscopy. Manual methods for this purpose are onerous, imprecise and highly subjective, thus requiring automated methods that perform this task in an objective and efficient way. In this paper, we propose a novel method to segment nucleus and cytoplasm of white blood cells...
This paper deals with the problem of segmenting a video shot into a background (still) mosaic and one or more foreground moving objects. The method is based on ego-motion compensation and background estimation. In order to be able to cope with sequences where occluding objects persist in the same position for a considerable portion of time, the papers concentrates on robust background estimation method...
For conveniently navigating and editing the news programs, it is very important to segment the video into meaningful units. The effective indexing of news videos can be fulfilled by the anchorperson shot because it is an indicator which denotes the occurrence of upcoming news stories. The paper presents a novel anchorperson detection algorithm based on spatio-temporal slice (STS). With STSpattern...
Adaptive background updating is an important step in motion segmentations of video sequences. However, the irregular distributions of background pixel values make the background modeling complicated. In this work, a method for background pixel classification based on the mean shift algorithm is proposed, which can classify the background pixels as single mode or multiple mode pixels so that different...
Shot detection is the first stage of video analysis. In this paper, we present a machine learning based shot detection approach using hidden Markov models (HMMs), in which both the color and shape clues are utilized. Its advantages are twofold. First, the temporal characteristics of different shot transitions are exploited and an HMM is constructed for each type of shot transitions, including cut...
The development in multimedia applications through the Internet has opened a new field of research in storing, handling, and retrieving digital videos. Video classification and segmentation are fundamental steps for efficient accessing, retrieving, browsing and compressing large amount of video data. The basic operation in analysis of heterogeneous video data is to design system that can accurately...
This paper proposes a DCT-based moving object extraction algorithm which is focused on rainy condition by change detection method. The DCT technique is used to decrease the rainy effect in order to construct a reliable background model. Then, we use change detection to classify pixels in video frame into the foreground region or background region so as to acquire an initial object mask. Besides, reflection...
In this paper, we present a new representation of sports video abstract-music sports-video (MSV), which provides exciting sports content accompanied with high quality background music for audiences and is available for high-quality audio-visual entertainment. We also propose a system generating MSV from user-provided sports video and music automatically. Firstly, the given sports video is segmented...
Temporal video segmentation is one of the fundamental and essential tasks in video processing, understanding and management. In this paper, we present an automatic method for segmenting the home videos into temporal logical units. We have developed a statistical framework using Markov chain Monte Carlo (MCMC) technique. The temporal scene boundaries are detected by maximizing the posterior probability...
Educational documentary videos play an important role in enriching learning experience. However, due to unstructured and linear features, documentary videos are much more difficult to access than text-based documents and have not been effectively utilized. In this paper, we propose a multimodal, hierarchical documentary video segmentation procedure based on image, audio and text understanding. The...
In this work, we propose a new super-resolution algorithm to simultaneously estimate all frames of a video sequence. The new algorithm is based on the Bayesian maximum a posteriori estimation. In contrast to other multi-frame super-resolution algorithms, the proposed algorithm does not include the motion in the observation model. Instead, transformations caused by the motion are used as a prior information...
Automatic video object segmentation and tracking is a challenging problem. In this paper, we introduce a new systematic method for fully automatic object segmentation and tracking using probabilistic fuzzy c-means and Gibbs random fields. The spatial segmentation is based on probabilistic fuzzy c-means clustering and Gibbs sampling. The obtained segmented mask is then refined by taking into account...
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