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Sport video annotation can help viewers easily browse sport video content and quickly find the hot events and highlights in a game. Although many annotation algorithms have been proposed, they are not suitable for practical implementation since the high complexity and the low precision rates are not acceptable. In this paper, a method of sport video temporal structure decomposition, which decomposes...
To make the moving object detection faster and more reliable, in this paper we present a novel method based on fast approximated SIFT descriptor. The main idea is to compute the feature descriptor of a key-point using the integral histogram of the surrounding squared region. The feature descriptor could be further used in the feature matching between two sequential frames in the image sequence. When...
Driver fatigue is a significant reason for many traffic accidents. We propose a novel multi-scale dynamic feature with feature level fusion for driver fatigue detection from facial image sequences. First, Gabor filters are employed to extract multi-scale and multi-orientation features from each image. Features of the same scale are then fused according to a fusion rule to produce a single feature...
This paper presents a spatiotemporal pyramid representation for recognizing facial expressions and hand gestures. This approach works by partitioning video sequence into increasingly fine subdivisions in the space and time domains and modeling the distribution of the local motion features inside each subdivision such that the set of motion features are mapped into spatial and temporal multi-resolution...
Video key frame extraction is a type of video abstraction, which is one of the key problems in video content indexing and retrieval. Key frame extraction aims at finding a small collection of salient images extracted from a video sequence for visual content summarization. In this paper we propose a video key frame extraction method based on spatial-temporal color distribution. First we construct a...
Video summarization is not only the key to effective cataloging and browsing video, but also as an embedded cue to trace video object activities. In this paper, a video summarization approach based on machine learning is developed for automatic video transition prediction. Several novel features are extracted to characterize video boundary, including cut, fade in, fade out and dissolve for facilitating...
Easily falling into local extremum, plateaus, and fast moving targets could't tracked, which are main handicap to mean shift application, especially in those cases to track the multi-articulated human body fine features. Based on the analysis of the causes of the mean shift, particle swarm optimization is introduced into the mean shift to solve this problem in this paper. Here, the mode estimation...
A novel method for face description by local multi-channel Gabor histogram sequence binary pattern (M-LGHSBP) is proposed. The motivation for the M-LGHSBP model is to find more rich and canonical texture measurement and deal with the high dimension problem of the local Gabor feature vector. Firstly, the normalized face image is sampled and blocked. Secondly, the blocked image is filtered by multi-orientation...
A novel approach for 3D motion capture data retrieval based on the Hierarchical Self Organizing Map (HSOM) is proposed. Given a query motion sequence, our goal is to search for all the similar motions from a database. Specifically, a feature vector based on the distribution of the human motion data is first extracted from each motion sequence in the database. Then, Singular Value Decomposition (SVD)...
This paper proposes a GPU based algorithm for extracting moving objects in real time. The whole process of the proposed approach is handled on GPU. GPU is used for acceleration and the proposed approach increases processing speed dramatically. The method uses a* component and b* component of CIELAB color space without extracting shadow areas as moving objects. It is robust to intensity changes because...
Due to the rapid development of motion capture technology, more and more human motion databases appear. In order to effectively and efficiently manage human motion database, human motion classification is necessary. In this paper, we propose an ensemble based human motion classification approach (EHMCA). Specifically, EHMCA first extracts the descriptors from human motion sequences. Then, singular...
SIFT (scale invariant feature transform) is used to solve visual tracking problem, where the appearances of the tracked object and scene background change during tracking. The implementation of this algorithm has five major stages: scale-space extrema detection; keypoint localization; orientation assignment; keypoint descriptor; keypoint matching. From the beginning frame, object is selected as the...
There has been a growth in demand for surveillance equipment to monitor people in indoor as well as outdoor environments. Furthermore, using guards to watch surveillance screens all the time is highly inefficient and thus automation of human monitoring can be more accurate and produce cost savings. The problem is challenging if we choose to use a passive non-invasive sensor such as vision. The specific...
Image information is widely used for the content-based retrieval of the image sequence. It is mainly used to segment a video by scene. Through this task, the structural video browsing can be achieved. The process that divides video into shots is called ldquovideo segmentationrdquo. For the video segmentation, detecting cut which is turn point of scene is called ldquocut detectionrdquo. In this paper,...
Efficiency and robustness are the two most important issues for multiobject tracking algorithms in real-time intelligent video surveillance systems. We propose a novel 2.5-D approach to real-time multiobject tracking in crowds, which is formulated as a maximum aposteriori estimation problem and is approximated through an assignment step and a location step. Observing that the occluding object is...
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