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We present an approach for detecting moving objects from a dynamic video sequence, using a stereo camera system. The detection of moving objects is a challenging problem, especially when backgrounds are also time-varying due to the concurrent changes of moving objects and backgrounds. Most of the previous approaches have been limited to the use of appearance information such as colors and 2D motions...
This paper proposes a robust detection method for circular objects in noisy and inhomogeneous contrast image. This method detects circular objects not by the difference in image intensities between the object interior and its surrounding, but by the separability and uniformity of the image intensity distributions as calculated by Bhattacharyya Coefficient. The proposed method can detect obscure and...
Airborne threats like aircrafts and missiles at long ranges appear as point or small targets in visible and infra-red image sequences. Size of the target in input image increases as it approaches towards the imaging sensor. Mathematical morphology is used to detect such targets but its performance is highly dependent on shape and size of structuring element. In this paper, we propose a novel robust...
Recently, there has been tremendous interest in the area of mobile Augmented Reality (AR) with applications including navigation, social networking, gaming and education. Current generation mobile phones are equipped with camera, GPS and other sensors, e.g., magnetic compass, accelerometer, gyro in addition to having ever increasing computing/graphics capabilities and memory storage. Mobile AR applications...
Recently, there has been tremendous interest in the area of mobile Augmented Reality (AR) with applications including navigation, social networking, gaming and education. Current generation mobile phones are equipped with camera, GPS and other sensors, e.g., magnetic compass, accelerometer, gyro in addition to having ever increasing computing/graphics capabilities and memory storage. Mobile AR applications...
Introduce a variation temporal differencing method, using this method we can judge the orientation and compute the centroid points of moving target. And then, giving a method to compute the pan & tilt rotation basing on the centroid point of moving target. The author used the variation temporal differencing method to design an automatic tracking system, this system has good performance in single...
We propose a robust abandoned object detection algorithm for real-time video surveillance. Different from conventional approaches that mostly rely on pixel-level processing, we perform region-level analysis in both background maintenance and static foreground object detection. In background maintenance, region-level information is fed back to adaptively control the learning rate. In static foreground...
We present an approach that directly uses curvature cues in a discriminative way to perform object recognition. We show that integrating curvature information substantially improves detection results over descriptors that solely rely upon histograms of orientated gradients (HoG). The proposed approach is generic in that it can be easily integrated into state-of-the-art object detection systems. Results...
A new algorithm is proposed to detect small objects by background suppression. It relies on a modified version of the nonlocal means filter introduced by Buades et al. for background prediction. Background pixels are estimated by a weighted average depending on the similarity between neighborhoods pixels. For background suppression, the similarity criterion is modified to be less sensitive to point...
We propose a robust approach for abandoned object detection in urban surveillance with over thousands of cameras. For such a large-scale monitoring based on intelligent video analysis, it is critical that a system be designed with careful control of false alarms. Our approach is based on proactive modeling of temporally static objects (TSO) such as cars stopping at red light and still pedestrians...
In this paper we propose an approach based on active contours to discriminate previously detected static foreground regions between abandoned and stolen. Firstly, the static foreground object contour is extracted. Then, an active contour adjustment is performed on the current and the background frames. Finally, similarities between the initial contour and the two adjustments are studied to decide...
In this paper, we present a novel robust technique for background subtraction in different complex conditions (e.g. sudden illumination changes, swaying leaves, and camera vibrations). Unlike the previous works, the proposed method utilizes multiple point pairs that exhibit a stable statistical intensity relationship as a background model. The intensity difference between pixels of the pair is much...
This paper presents an object detection algorithm using multiple cameras, which is robust in the presence of cast shadows. The information fusion is based on homography mapping of the foreground regions to a top view image. The homography is based on multiple planar planes parallel to the ground plane. Two novel approaches to estimating such homography have been proposed. The results on an open video...
A biologically inspired approach for automated visual tracking is proposed. In this approach it is hypothesized that target initialization and tracking are a consequence of saliency mechanisms that guide the deployment of visual attention. The recently proposed discriminant center-surround saliency model, is used to derive the tracking framework. In this framework, automatic tracker initialization...
To accomplish real-time tracking of moving objects requirements, and overcome the defect of occlusion in the process of tracking moving object, this paper presents a set of real-time tracking system. The tracking system uses a combination of camshift and kalman filter algorithm. When the moving object is a large area blocked, the velocity of moving object is applied linear prediction to kalman filter...
This paper propose an object recognition method based on template match that uses both gradient and LBP feature as the template feature. We also design a binary representation and quick bitwise operation for the proposed approach.
In this research study, we propose a divided planar-object detection method for augmented reality(AR) applications. There are mainly two types of camera-registration methods for AR applications: marker-based methods, and natural-feature-based methods. In addition, the latter methods are classified into visual SLAM and object detection methods. With respect to object detection methods, particularly...
Facial occlusions, due for example to sunglasses, hats, scarf, beards etc., can significantly affect the performance of any face recognition system. Unfortunately, the presence of facial occlusions is quite common in real-world applications especially when the individuals are not cooperative with the system such as in video surveillance scenarios. While there has been an enormous amount of research...
This work introduces techniques to facilitate large-scale Augmented Reality (AR) experiences in unprepared outdoor environments. We develop a shape-based object detection framework that works with limited texture and can robustly handle extreme illumination and occlusion issues. The contribution of this work is a purely geometric approach for detecting marker-like objects under difficult and realistic...
Cooperation is a key concept used in multi-robot systems for performing complex tasks. In swarm robotics, a self-organized cooperation is applied, where robots with limited intelligence cooperate and interact locally to build up the desired global behavior. In this paper, we are studying a mobile object tracking scenario performed by a swarm of robots. The robustness, scalability and flexibility of...
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