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Realizing the automated and online detection of crowd anomalies from surveillance CCTVs is a research-intensive and application-demanding task. This research proposes a novel technique for detecting crowd abnormalities through analyzing the spatial and temporal features of the input video signals. This integrated solution defines an image descriptor that reflects the global motion information over...
To determine the real-time traffic state accurately in road network or intersections, traffic state identification method is proposed based on image processing technology. During the image process, by analyzing the image texture features, the multi-scale block local binary patterns are taken as the features. The road traffic state identification model is established based on support vector classification...
Recently, there are increasing interests in inferring mirco-expression from facial image sequences. For micro-expression recognition, feature extraction is an important critical issue. In this paper, we proposes a novel framework based on a new spatiotemporal facial representation to analyze micro-expressions with subtle facial movement. Firstly, an integral projection method based on difference images...
To understand which concepts are visualizable and to what extent they can be visualized are worthwhile for multimedia and computer vision research. Unfortunately, few previous works have ever touched such topics. In this paper, we propose an unified model to automatically identify visual concepts and estimate their visual characteristics, or visualness, from a large-scale image dataset. To this end,...
Shape features are one of the most popular low-level image representations for computer vision (CV) tasks such as template matching, image collaboration and object recognition. In this paper, an application-originated research has been introduced for extracting representative shape characteristics from challenging real-world scenes based on the image “textures”. The proposed new approach starts from...
Real-world environment introduces many variations into video recordings such as changing illumination and object dynamics. In this paper, a technique for abstracting useful spatio-temporal features from graph-based segmentation operations has been proposed. A spatio-temporal volume (STV)-based shape matching algorithm is then devised by using the intersection theory to facilitate the definition and...
In content-based image retrieval systems, the invariance to geometrical transformations is one of the most desired properties. In this paper, a kind of rotation, scaling and translation (RST) invariant feature for image retrieval is investigated, and a new method is proposed to extract this type of feature. The proposed scheme first detects the scale invariant key points in images, and then utilizes...
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