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Key frame selection is important to dense 3D reconstruction, especially for unordered image sets. A novel method for key frame selection from unordered image sets is proposed based Distance Depedent Chinese Restaurant Process (DDCRP). First, a bag-of-features word package is constructed to describe each image in a document-like manner, which can be dealt with by the DDCRP model. Second, the overlapping...
With widening interests in using model organisms for reverse genetic approaches and biomimmetic microrobotics, motility phenotyping of the nematode Caenorhabditis elegans is expanding across a growing array of locomotive environments. One ongoing bottleneck lies in providing users with automatic nematode segmentations of C. elegans in image sequences featuring complex and dynamic visual cues, a first...
This paper proposes a method of gait recognition using not only shape feature but also motion feature from silhouette image sequences. The inner silhouette motion called pseudo motion is constructed by dividing the silhouette shape into small clusters and by computing many-to-many correspondence via earth mover's morphing framework. The raw pseudo motion, however, tends to be locally fluctuated in...
This paper presents an in-depth analysis of the SIFT and SURF feature detection and matching techniques in characterizing natural environments for vision based navigation problems, in particular, the performance of feature extraction algorithms and matching when both visual and infrared data are used. With successful utilization of both feature extraction methods on different characteristic images,...
Early fire detection is crucial to minimise damage and save lives. Video surveillance smoke detectors do not suffer from transport delays and can cover large areas. The smoke detection on images is, however, a difficult problem due the variability of smoke density, lighting conditions, background clutter, and unstable patterns. In order to solve this problem, we propose a novel unsupervised object...
Maneuvering target tracking is a big challenge to the performance of a visual tracker. The paper proposes a method to keep the tracker robust to target maneuvering by selecting discriminative features from a large feature space, and constructing a velocity motion model with adaptive noise variance. Furthermore, the feature selection procedure is embedded into the particle filtering process with the...
There is an increased interest in developing an automatic facial expression analysis to recognize and model real human faces. In this paper, a local model-based approach for extraction of facial feature points from 2D still images and feature points tracking in image sequences are presented. It presents an algorithm that extracts the local oriented edges of intransient facial features (eyebrows, eyes,...
The application of learning-based vision techniques to real scenarios usually requires a tunning procedure, which involves the acquisition and labeling of new data and in situ experiments in order to adapt the learning algorithm to each scenario. We address an automatic update procedure of the L2boost algorithm that is able to adapt the initial models learned off-line. Our method is named UAL2Boost...
This paper addresses the problem of mapping three dimensional environments from a sequence of images taken by a calibrated camera, and simultaneously generating the camera motion trajectory. This is the Monocular SLAM problem in robotics, and is akin to the Structure from Motion (SFM) problem in computer vision. We present a novel map-aided 6-DOF relative pose estimation method based on a new formulation...
In this paper, Human Visual System (HVS) characteristics are modeled using Lee and Lu's Fuzzy- BP network for the purpose of image watermarking. The Fuzzy-BP network is trained by 27 inference rules comprising of three input HVS features namely luminance sensitivity, edge sensitivity computed using threshold and contrast sensitivity computed using variance. The Fuzzy-BP network block wise produces...
Non-rigid characteristics of the human body and the diversification of human articulations are the two challenging problems in pedestrian detection, especially in cluttered scenes that commonly involve multiple people, such as surveillance cameras. Moreover occlusion and body changes also increase the difficulty of the people detecting. The general pictorial structure can divide human body into some...
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...
Lipreading is applied to synthesize speech for the speech-impaired people. To get a higher recognition result, data fusion with weighting coefficients at feature level is used to integrate the lip information from different kinds of lip features. Experiments are carried out based on HMM with different states and Gaussian mixture component in a small database for speaker-dependent case. From the recognition...
Hand gesture interpretation is an open research problem in Human Computer Interaction (HCI), which involves locating gesture boundaries (Gesture Spotting) in a continuous video sequence and recognizing the gesture. Existing techniques model each gesture as a temporal sequence of visual features extracted from individual frames which is not efficient due to the large variability of frames at different...
We present Transitive Closure based visual word formation technique for obtaining robust object representations from smoothly varying multiple views. Each one of our visual words is represented by a set of feature vectors which is obtained by performing transitive closure operation on SIFT features. We also present range-reducing tree structure to speed up the transitive closure operation. The robustness...
In this paper, we propose a method to model the material constants (Young's modulus) of the skin in subregions of the face from the motion observed in multiple facial expressions and present its relevance to an image analysis task such as face verification. On a public database consisting of 40 subjects undergoing some set of facial motions associated with anger, disgust, fear, happy, sad, and surprise...
In intelligent surveillance field, the numerous methods have been proposed for foreground extraction from a stationary or dynamic background from a general video sequence. It is very difficult for the proposed methods to have both high accuracy, low computational complexity and less memory requirements. Unlike previous approaches to object detection which detect objects by building adaptive models...
In this paper we tackle the problem of detecting individual human actions in video sequences. While the most successful methods are based on local features, which proved that they can deal with changes in background, scale and illumination, most existing methods have two main shortcomings: first, they are mainly based on the individual power of spatio-temporal interest points (STIP), and therefore...
This paper presents a novel approach for unexpected behavior recognition in image sequences with attention to high density crowd scenes. Due to occlusions, object-tracking in such scenes is challenging and in cases of low resolution or poor image quality it is not robust enough to efficiently detect abnormal behavior. The wide variety of possible actions performed by humans and the problem of occlusions...
This paper considers the problem of detecting actions from cluttered videos. Compared with the classical action recognition problem, this paper aims to estimate not only the scene category of a given video sequence, but also the spatial-temporal locations of the action instances. In recent years, many feature extraction schemes have been designed to describe various aspects of actions. However, due...
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