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In this paper we examine the causes of one of the major shortcomings of current natural feature registration approaches, failure to register when the camera's view approaches parallel to the marker. The methods used by current registration algorithms in the attempt to overcome this problem are reviewed, and a novel tracking based approach called the Optical-flow Perspective Invariant Registration...
Pedestrian detection is an important field in computer vision with applications in surveillance, robotics and driver assistance systems. The quality of such systems can be improved by the simultaneous use of different sensors. This paper proposes three different fusion techniques to combine the advantages of two vision sensors -- a far-infrared (FIR) and a visible light camera. Different fusion methods...
This paper presents a scene classification method using criterion mining and adaptive integration. Since scene classification requires scene composition and shift-invariant similarity of fine parts, the latter two are represented by global and local Kernel Principal Component Analysis (KPCA), respectively. In addition, the reconstruction errors obtained with either KPCA are integrated adaptively with...
Visual activity detection of lip movements can be used to overcome the poor performance of voice activity detection based solely in the audio domain, particularly in noisy acoustic conditions. However, most of the research conducted in visual voice activity detection (VVAD) has neglected addressing variabilities in the visual domain such as viewpoint variation. In this paper we investigate the effectiveness...
The automated extraction of roads from aerial imagery can be of value for tasks including mapping, surveillance and change detection. Unfortunately, there are no public databases or standard evaluation protocols for evaluating these techniques. Many techniques are further hindered by a reliance on manual initialisation, making large scale application of the techniques impractical. In this paper, we...
Multiresolution representations and Subspace analysis have been widely accepted in the face recognition systems. This research paper combines the benefits and presents the feature extraction method using Discrete Wavelet Transform (DWT) and Independent Component Analysis (ICA). The DWT provides multiresolution representations and are effective in analyzing the information content of the image and...
Thermal-infrared images have superior statistical properties compared with visible-spectrum images in many low-light or no-light scenarios. However, a detailed understanding of feature detector performance in the thermal modality lags behind that of the visible modality. To address this, the first comprehensive study on feature detector performance on thermal-infrared images is conducted. A dataset...
This paper describes a scene invariant crowd counting algorithm that uses local features to monitor crowd size. Unlike previous algorithms that require each camera to be trained separately, the proposed method uses camera calibration to scale between viewpoints, allowing a system to be trained and tested on different scenes. A pre-trained system could therefore be used as a turn-key solution for crowd...
This paper presents a framework for Visual Attention Detection in maritime scenes. The focus is to provide an early processing stage for high resolution images captured by maritime surveillance platforms. The framework groups multiple low-level features that are designed specifically for maritime scenarios with different distance measurements. Integrated in the framework is a detector for sea and...
This paper presents a comparative study of different texture extraction methods for the automatic classification of the tear film lipid layer based on the categories enumerated by Guillon. From a photography of the eye, a region of interest is detected and its low-level features are extracted, generating a feature vector that describes it, to be finally classified in one of the target categories....
In this paper a new method for the measurement of near-shore wave height from a digital video sequence is presented. The method identifies the location of the main wave break zones and then detects shoaling waves inside the detected break zone and estimate their heights. A geometric rectification is then used to convert the height measurement from image pixels to metres. Validation of the algorithm...
Point-pattern matching of minutiae is the most common method used in fingerprint biometrics, but it is generally insufficient by itself. It has particular limitations in matching partial prints or in secure (biocryptographic) matching. Here, we add structure with a new spatial graph represention of a fingerprint, with minutiae as nodes. Using a sample of fingerprint graphs extracted from the FVC2002...
In this paper, real time surveillance system is presented for an efficient identification of a person as an intruder or not in the inhibited location by multi-algorithmic approach. This system is aided with both wired and wireless sensor network. The Wireless Sensor Network detects the presence of person using PIR sensor and identifies the person with RFID and the verification is assured by using...
Video analysis aiming at efficient pedestrian detection is an important research area in computer vision and robotics. Although this is a well studied topic, successful detection still remains a challenge in outdoor, low resolution images. We present efficient detection metrics which consider the fact that human movement presents some characteristic patterns. Unlike many methods which perform an intra-blob...
This paper investigates the effectiveness of state-of-the-art classification algorithms to categorise road vehicles for an urban traffic monitoring system using a multi-shape descriptor. The analysis is applied to monocular video acquired from a static pole-mounted road side CCTV camera on a busy street. Manual vehicle segmentation was used to acquire a large (>2000 sample) database of labelled...
We address the problem of automated fingerprints-based person identification from poor-quality fingerprints. Our solution includes the definition of a region of interest centered over the fingerprint at a reference point. From this region of interest a feature vector is computed that is invariant to some geometrical transforms but also to point transforms of the gray levels in the region of interest...
Scene classification in indoor and outdoor environments is a fundamental problem to the vision and robotics community. Scene classification benefits from image features which are invariant to image transformations such as rotation, illumination, scale, viewpoint, noise etc. Selecting suitable features that exhibit such invariances plays a key part in classification performance. This paper summarizes...
This paper presents a method for ship detection using texture statistics from optical satellite images. The proposed method focuses on the extraction of ship candidates. First, a structural texture descriptor derived from local multiple patterns is introduced to describe image texture features, and then two statistical histograms are generated by quantizing texture features to describe the texture...
Local image feature extractors that select local maxima of the determinant of Hessian function have been shown to perform well and are widely used. This paper introduces the negative local minima of the determinant of Hessian function for local feature extraction. The properties and scale-space behaviour of these features are examined and found to be desirable for feature extraction. It is shown how...
Modelling events in densely crowded environments remains challenging, due to the diversity of events and the noise in the scene. We propose a novel approach for anomalous event detection in crowded scenes using dynamic textures described by the Local Binary Patterns from Three Orthogonal Planes (LBP-TOP) descriptor. The scene is divided into spatio-temporal patches where LBP-TOP based dynamic textures...
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