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Most man-made indoor and urban scenes are composed of a set of orthogonal and parallel planes. In robotics and computer vision, these scenes typically represented by the Manhattan-World model. The accurate estimation of the Manhattan Frame, which consists of three orthogonal directions being used to represent the Manhattan-World, plays an important role in many applications, such as SLAM, scene understanding...
In this paper, we present a visual learning framework to retrieve a 3D model and estimate its pose from a single image. To increase the quantity and quality of training data, we define our simulation space in the near infrared (NIR) band, and utilize the quasi-Monte Carlo (MC) method for scalable photorealistic rendering of manufactured components. Two types of convolutional neural network (CNN) architectures...
Asynchronous event-based sensors present new challenges in basic robot vision problems like feature tracking. The few existing approaches rely on grouping events into models and computing optical flow after assigning future events to those models. Such a hard commitment in data association attenuates the optical flow quality and causes shorter flow tracks. In this paper, we introduce a novel soft...
Understanding human behavior is crucial for planning evacuation strategies when an emergency occurs. The social force model, which is a successful quantitative model, has been widely used in investigating human behavior. In this paper, we propose a gradient descent based parameter optimization method to learn the parameters of the social force model from experimental data. Although the original social...
In this paper, we propose a deep convolutional neural network model for in-bed behavior recognition and bed-exit prediction. This model extracts features for training from depth images taken by depth cameras in two categories: in-bed images taken several time intervals before a patient gets out of bed, and usual in-bed activity images. The depth camera-based model features grayscale and low-resolution...
The construction of a model of the background of a scene still remains as a challenging task in video surveillance systems, in particular for moving cameras. This work presents a novel approach for constructing a panoramic background model based on competitive learning neural networks and a subsequent piecewise linear interpolation by Delaunay triangulation. The approach can handle arbitrary camera...
The unprecedented amounts of data generated from large scientific simulations impose a grand challenge in data analytics, and I/O simply becomes a major performance bottleneck. To address this challenge, we present an application-aware I/O optimization technique in support of interactive large-scale scientific visualization. We partition a scientific data into blocks, and carefully place data blocks...
Human actions recognition has been one of the most popular subject areas in computer vision. Recently, the usage of depth cameras which are capable of generating three dimensional data enabled more complex human actions to be recognized. In this study, the problem of tennis actions recognition using a depth camera is tackled and a three dimensional tennis actions dataset has been created. To be able...
In this paper, we investigate the use of Kalman filter to enable robust tracking based on an efficient pose estimation algorithm, namely the four-point algorithm. Pose estimation is very useful in vision-based system control, for example in automatic driving and virtual reality inputs. Firstly, we have implemented a four-point pose estimation method with a personal computer. This estimation algorithm...
In this paper a controller for PTZ cameras based on an unsupervised neural network model is presented. It takes advantage of the foreground mask generated by a non-parametric foreground detection subsystem. Thus, our aim is to optimize the movements of the PTZ camera to attain the maximum coverage of the observed scene in presence of moving objects. A growing neural gas (GNG) is applied to enhance...
We presented a new algorithm of underwater bubble recognition, which employs background modeling, image segmentation and pattern recognition. After obtaining underwater bubble images, we can separate single bubble from it manually and construct the database. Having computed Hu moment of samples for training and test, we can get the threshold and store. Then inputting the other images of sample, we...
In this paper, a new method for mapping textures onto a 3D model produced by a multi-view reconstruction pipeline is proposed. A Markov Random Field (MRF) is constructed so as to define each triangle face as a node. An optimal labeling is estimated by globally minimizing an energy function defined on the MRF using graph cuts algorithms. This labeling assigns exactly one view to each triangle face...
With the rapid improvement of three-dimensional scanner hardware technology, the accuracy of the point cloud is getting higher and higher, so the number of point-clouds is increasing shar ply, which greatly affects the speed and performance of point-cloud registration. Based on feature matching and ICP algorithm, a 3D point-cloud model stitching algorithm by using Kinect sensors scanning was proposed...
Chest wall mobility assessment is an important parameter in diagnosing pulmonary disorders. The purpose of this study is to examine and compare variations in thoracic and abdominal volumes based on changes in chest expansion that can be used as a clinical tool in pulmonary function studies. A newly proposed optical camera system utilizing a set of markers placed on subjects' thoracic and abdominal...
Natural Steganography (NS) uses the concept of cover-source switching to provide good undetectability performances [1]. The sensor noise of the source (camera) for a given ISO sensitivity ISO1 is first modeled as an independent Gaussian distribution for each photo-site, then the embedding mimics a switch to another sensitivity ISO2(> ISO1). Because the embedding has to be performed on developed...
Multi-frame image super-resolution (SR) is an image processing technology applicable to any digital, pixilated camera that is limited, by construction, to a certain number of pixels. The objective of SR is to utilize signal processing to overcome the physical limitation and emulate the “capabilities” of a camera with a higher-density pixel array. SR is well known to be an ill-posed problem and, consequently,...
Automatic tracking of rodents' behaviors over time in their home cages is of great interest in psycho-physiological studies. The commercially-available animal monitoring systems use RGB videos or bio-potential signals to monitor behaviors of animals when exploring their surroundings. The based models of these devices starts from several thousands of dollars and the cost would increase if extra analysis...
We present an algorithm that finds planar structures in a Manhattan world from two pictures taken from different viewpoints with unknown baseline. The Manhattan world assumption constrains the homographies induced by the visible planes on the image pair, thus enabling robust reconstruction. We extend the T-linkage algorithm for multistructure discovery to account for constrained homographies, and...
Appearance based person re-identification in real-world video surveillance systems is a challenging problem for many reasons, including ineptness of existing low level features under significant viewpoint, illumination, or camera characteristic changes to robustly describe a person's appearance. One approach to handle appearance variability is to learn similarity metrics or ranking functions to implicitly...
The future of user interfaces will be dominated by hand gestures. In this paper, we explore an intuitive hand gesture based interaction for smartphones having a limited computational capability. To this end, we present an efficient algorithm for gesture recognition with First Person View (FPV), which focuses on recognizing a four swipe model (Left, Right, Up and Down) for smartphones through single...
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