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In this paper a novel view-invariant movement recognition method is presented. A multi-camera setup is used to capture the movement from different observation angles. Identification of the position of each camera with respect to the subject's body is achieved by a procedure based on morphological operations and the proportions of the human body. Binary body masks from frames of all cameras, consistently...
In this paper we propose two alternatives to overcome the natural asynchrony of modalities in Audio-Visual Speech Recognition. We first investigate the use of asynchronous statistical models based on Dynamic Bayesian Networks with different levels of asynchrony. We show that audio-visual models should consider asynchrony within word boundaries and not at phoneme level. The second approach to the problem...
Locating the vehicle license plate plays an important role in the vehicle license plate automatic recognition system, At present license plate gray feature and texture feature were considered in the most license plate location methods, however, these methods have weak adaptability in different environment. To solve these problems, license plate location based on singular value feature is proposed...
Recognition of degraded characters is a challenging problem in the field of document image analysis. Two main reasons for degradation of characters are due to noise scanning and intrinsic degradation caused by font variations. The degradation of characters is mostly in the form of characters being broken at several places which hinders their recognition of OCR systems. Many OCRs have been designed...
Wavelet packet analysis method is appropriate to process nature texture signal and a hidden Markov model has good learning interpretability and needs only small training samples. A wavelet packet-HMM-based method on road surface state recognition was proposed. The wavelet packet analysis was adapted to extract characteristic entropies from the image signals. Thus, four kinds of data on road surface...
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...
An agent-based HMM position tagging (AHPT) model was proposed for Chinese person name recognition. The model unified unknown word identification and person name recognition as a single tagging task. Based on context pattern, special name table and position dependent information, the model could integrate both the internal information and surrounding contextual clues for name entity recognition (NER)...
Recognizing human activities from image sequences is an active area of research in computer vision. Most of the previous work on activity recognition focuses on recognition from video clips that show only single activities. There are few published algorithms for segmenting and recognizing complex activities that are composed of more than one single activity. In this paper, we present a novel HMM-based...
Humanoid developments express the need for intelligent learning systems that can automatically realize behavior acquisition and symbol emergence. In the framework of mimesis model, we present an unsupervised dynamic HMM-based algorithm in order to analyze vectorial motion data. The efficiency of this algorithm is demonstrated by segmenting continuous sequence of real movements. We also propose to...
The recognition of events in video data is a subject of much current interest. In this paper, we address several issues related to this topic. The first one is overfitting when very large feature spaces are used and relatively small amounts of training data are available. The second is the use of a framework that can recognise events at different time scales, as standard hidden Markov model (HMM)...
We present a framework for detecting and recognizing human activities for outdoor video surveillance applications. Our research makes the following contributions: For activity detection and tracking, we improve robustness by providing intelligent control and fail-over mechanisms, built on top of low-level motion detection algorithms such as frame differencing and feature correlation. For activity...
This paper presents a new system for teachers' natural complex action recognition in the smart classroom in order to realize an intelligent cameraman and virtual mouse. First, the system proposes a hybrid human model and employs a 2-order B-spline function to detect the two shoulder joints in the silhouette image to obtain the basic motion features including the elbow angles, motion parameters of...
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