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We propose a method for automatic emotion recognition as part of the FERA 2011 competition. The system extracts pyramid of histogram of gradients (PHOG) and local phase quantisation (LPQ) features for encoding the shape and appearance information. For selecting the key frames, K-means clustering is applied to the normalised shape vectors derived from constraint local model (CLM) based face tracking...
A novel neural network method to predict the spectral signature in the predicted meteorological image is presented here. Back propagation algorithm has been used in this work. Based on computation cost, three different dimensional feature vectors are provided from two consecutive images as input to neural net for training and testing. Various kinds of testing are made depending upon position of predicted...
We introduce the questionable observer detection problem: Given a collection of videos of crowds, determine which individuals appear unusually often across the set of videos. The algorithm proposed here detects these individuals by clustering sequences of face images. To provide robustness to sensor noise, facial expression and resolution variations, blur, and intermittent occlusions, we merge similar...
The emphasis is on the key-frame extraction technique in content-based video retrieval. Dealing with problems existed in the traditional clustering algorithms, an improved shots key-frame extraction algorithm based on fuzzy C-means clustering is presented. Using the color feature information in the video frames, and then through the improvement of the clustering algorithm of video sequences to acquire...
With the rapid development of web video application, video similarity search has become a hot research field in content-based video retrieval. Many efforts have been carried out to improve the effectiveness and efficiency of similarity search in large database. In order to solve two challenging problems: similarity measurement and search method, a novel efficient VSS approach is proposed in this paper...
An improved shots clustering key-frame extraction algorithm based on entropy is presented. Using the color information in the video frames, the algorithm looks every frame of a shot as a special sample and selects appropriate feature. And then through the improvement of the clustering analysis of video sequences to acquire the center value of various classes and the membership degree of every sample...
Many applications in media production need information about moving objects in the scene, e.g. insertion of computer-generated objects, association of sound sources to these objects or visualization of object trajectories in broadcasting. We present a GPU accelerated approach for detecting and tracking salient features in image sequences and we propose an algorithm for clustering the obtained feature...
In this paper, we propose a macro-observation scheme for unusual event detection in daily life, where motions in time-space domain are described by a global representation and individual activities do not have to be defined and modeled beforehand. The proposed representation records the time-space energy of motions of all moving objects in a scene without segmenting individual object parts or tracking...
Anomaly detection in crowd scene is very important because of more concern with people safety in public place. This paper presents an approach to automatically detect abnormal behavior in crowd scene. For this purpose, instead of tracking every person, KLT corners are extracted as feature points to represent moving objects and tracked by optical flow technique to generate motion vectors, which are...
This paper presents a novel slice-based approach to detect pedestrians in still images. A pedestrian is divided into limited numbers of slice-based sub-regions through a spatio-temporal slice processing. First, sub-regions of interest are detected in different spatio-temporal slice images. Then, a clustering algorithm is proposed to combine these sub-regions into individual pedestrians based on their...
We present an efficient technique based on histogram evolution for summarizing video sequences to make them more amenable to browsing and retrieval. First, a ground-truth database of videos is generated in which the shot breaks are detected by human subjects and numbered in order. Three types of histogram are then used to capture the characteristics of color content containing in the video frames...
In this paper we develop a novel approach called the compensated HS (CHS) optical flow estimation algorithm to improve the precision of the large displacement optical flow field. For the lack of the higher order term in the optical flow constraint equation, the traditional optical flow estimation based on the first-order gradient always produce the optical flow field with obvious error in the case...
Key frames play a very important role in video retrieval. In this paper, we introduce a novel method to extract key frames to represent video shot based on connectivity clustering. Compared with other methods, the proposed method can dynamically divide the frames into clusters depending on the content of shot, and then the frame closest to the cluster centroid is chosen as the key frame for the video...
In this paper, we propose a system to recognize alphabet characters (A-Z) and numbers (0-9) in real-time from stereo color image sequences using Hidden Markov Models (HMMs). Additionally, a robust method for hand tracking in a complex environment using Mean-shift analysis in conjunction with 3D depth map is introduced. The depth information solve the overlapping problem between hands and face, which...
Pulmonary radiographs are essential tools to the evaluation and diagnosis of suspected infections of the lower respiratory system. Interpretation of a radiograph in the clinical context is a valuable diagnostic adjunct to the selection and the management of a specific clinical protocol for therapy. The key element in the proper diagnosis of a bacterial pulmonary infection is the analysis of the radiographic...
The amount of online video is increasing tremendously nowadays. For the convenience of information retrieval, video similarity search has become an important research issue in content-based video retrieval. There is still no satisfying scalable fast similarity search method for large database. In order to solve two challenging problems: similarity measure and fast search, a novel efficient video similarity...
In this paper we propose a new method for human action categorization by using an effective combination of novel gradient and optic flow descriptors, and creating a more effective codebook modeling the ambiguity of feature assignment in the traditional bag-of-words model. Recent approaches have represented video sequences using a bag of spatio-temporal visual words, following the successful results...
This paper presents a novel approach to skim and describe 3D videos. 3D video is an imaging technology which consists in a stream of 3D models in motion captured by a synchronized set of video cameras. Each frame is composed of one or several 3D models, and therefore the acquisition of long sequences at video rate requires massive storage devices. In order to reduce the storage cost while keeping...
In this paper, we propose a framework for unsupervised analysis of human behavior based on manifold learning. First, a pairwise human posture distance matrix is calculated from a training action sequence. Then, the isometric feature mapping (Isomap) algorithm is applied to construct a low-dimensional structure from the distance matrix. The data points in the Isomap space are consequently represented...
Most recent facial expressions recognition systems only work well with frontal face images. However, subjects do not always face front. With this in mind, we propose in this paper a method for pose-robust facial expressions recognition. Active appearance models (AAMs) are used for face tracking to extract pose-robust facial feature points. However, AAM has accuracy problems with face tracking when...
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