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We propose a joint object pose estimation and categorization approach which extracts information about object poses and categories from the object parts and compositions constructed at different layers of a hierarchical object representation algorithm, namely Learned Hierarchy of Parts (LHOP) [7]. In the proposed approach, we first employ the LHOP to learn hierarchical part libraries which represent...
In this paper we are proposing a novel computer vision system that can recognize expression of pain in videos by analyzing facial features. Usually pain is reported and recorded manually and thus carry lot of subjectivity. Manual monitoring of pain makes difficult for the medical practitioners to respond quickly in critical situations. Thus, it is desirable to design such a system that can automate...
With the wide use of steganographic techniques, several security challenges emerge, e.g. criminals and network intruders can hide any information they want into legitimate multimedia data and exchange it over the Internet. This requires network designers and service providers to investigate new tools for detecting such misuse. In this paper, we explore a detection method based on neural network approach...
The video key frame extraction technology is one of the important parts of content-based video retrieval. And the mainstream of key frame extraction is the algorithm based on clustering. The basic idea is: the video frames are grouped in accordance with the correlation of the visual content by clustering, and then we extract the most representative frame from each group as a key frame. In this paper,...
The development of a fully automatic facial expression recognition system is an open problem. Its implications are very important, with applications ranging from machine intelligence and interaction to psychology research. In order to obtain a viable system, it is necessary to get valid parameters to characterize the facial expression in an image or a video sequence. Several different techniques have...
This work is focused on the modeling and development of a CBIR (Content-based image retrieval) system applied to the recovery of digital medical images of a human body, denominated M-CBIR. This model is composed on two methodologies: features extraction techniques and metric data structures. When this set of techniques is applied to the search of different human body regions, it can retrieve the most...
Research on image retrieval technology based on color feature, for the color histogram with a rotation, translation invariance of the advantages and disadvantages of lack of space, a color histogram and color moment combination image retrieval. The theory is a separate color images and color histogram moment of extraction, and then two methods of extracting color feature vector weighted to achieve...
Document clustering is the process of partitioning a set of unlabeled n documents into clusters such that documents in each cluster share some common concepts. Each concept is conveniently represented by some key terms. Using words as features, text data are represented as a vector in a very high dimensional vector space. However, most documents are sparse vectors, for example, more than ten thousand...
This paper presents a face-tracking algorithm based on particle filter framework. Firstly, a target state is obtained using conventional color histograms. Secondly, a tracking method is proposed on the basis of seven moment invariants, and another state vector is also computed using this approach. Furthermore, the weights of the two state vectors are computed according to Euclidean distance between...
Based on the analysis of color histogram for image retrieval, a new descriptor, bit-plane distribution feature (BPDF), is proposed in this paper. The image is firstly divided into eight bit-planes. Meantime, the Gray code of bit-planes is used to avoid the effect of changes in the intensity values on bit-planes. Then, according to the distribution of each bit-plane, a feature vector is constructed...
LPP (locality preserving projection), as a linear version of manifold learning algorithm, has attracted considerable interests in recent years. For real time applications, the response time is required to be as short as possible. In this paper, a new local image descriptor-LPP-HOG (histograms of oriented gradients) for fast human detection is presented. We employ HOG features extracted from all locations...
Human motion self-occlusion due to motion overlapping in the same region is a daunting task to solve. Various motion-recognition methods either bypass this problem or solve this problem in complex manner. Appearance-based template matching paradigms are simpler and hence faster approaches for activity analysis. In this paper, we concentrate on motion self-occlusion problem due to motion overlapping...
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