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This paper presents the design and computational modelling of a virtual simulator of a multitool, for training vocational skills in a hands-on way. Here we describe the audio-visual-haptic elements for the customized simulation interfaces for training carpentry tools and skills and the computational mathematical model to render haptic feedback for these actions. Finally the paper will explain the...
Minimally invasive surgery is a specialized surgical technique that permits vascular interventions through very small incisions. It minimizes the patient's trauma and permits a faster recovery compared to traditional surgery. Although traditional invasive surgery training system can complete general training work, real-time performance and accuracy of most training system failed to meet the requirements...
Coronary artery disease is the leading cause of death in the world. In this research, we propose an algorithm based on the machine learning techniques to predict the risk of coronary artery atherosclerosis. A ridge expectation maximization imputation (REMI) technique is proposed to estimate the missing values in the atherosclerosis databases. A conditional likelihood maximization method is used to...
Although emotional state recognition from voice has been extensively studied, there is not much effort focusing on the online emotion recognition. Since duration and intensity of emotional experiences change over time it is hard to employ existing static transition models while monitoring emotional states especially in an online setting. To overcome this difficulty we introduce a method which incorporates...
Inferring scene depth from a single monocular image is an essential component in several computer vision applications such as 3D modeling and robotics. This process is an ill-posed problem. To tackle this challenging problem, previous efforts have been focusing on exploiting only global or local depth aware properties. We propose a model that incorporates both of them to obtain significantly more...
This paper addresses 3D shape recognition. Recent work typically represents a 3D shape as a set of binary variables corresponding to 3D voxels of a uniform 3D grid centered on the shape, and resorts to deep convolutional neural networks (CNNs) for modeling these binary variables. Robust learning of such CNNs is currently limited by the small datasets of 3D shapes available - an order of magnitude...
We introduce a novel robust hybrid 3D face tracking framework from RGBD video streams, which is capable of tracking head pose and facial actions without pre-calibration or intervention from a user. In particular, we emphasize on improving the tracking performance in instances where the tracked subject is at a large distance from the cameras, and the quality of point cloud deteriorates severely. This...
3D sketch-based 3D model retrieval is to retrieve similar 3D models using users' hand-drawn 3D sketches as input. Compared with traditional 2D sketch-based retrieval, 3D sketch-based 3D model retrieval is a brand new and challenging research topic. In this paper, we employ advanced deep learning method and propose a novel 3D sketch based 3D model retrieval system. Our system has been comprehensively...
We propose a novel method for the recognition of objects that match a given 3D model in large-scale scene point clouds captured in indoor environments with a laser range finder. Since large-scale indoor point clouds are greatly damaged by noise such as clutter, occlusion, hole, and measurement errors, it is difficult to exactly identify local correspondences between points in a target model point...
We tackle the problem of learning a rotation invariant latent factor model when the training data is comprised of lower-dimensional projections of the original feature space. The main goal is the discovery of a set of 3-D bases poses that can characterize the manifold of primitive human motions, or movemes, from a training set of 2-D projected poses obtained from still images taken at various camera...
Analyze the characteristic of three-dimensional scene visualization and regulation of scene change in flight simulation system, which is the basis of implementation of terrain reconstruction. Give the related mathematics model of terrain visualization. In order to resolve the problem that three-dimensional scene could not be reconstructed fast because of large-scale terrain data, present a procedure...
We present an unsupervised method for discovering objects from depth information. Our method can identify new common objects appearing in different depth images. We use 2D bounding box proposals to detect candidate locations of objects in each depth image, and then retrieve the corresponding 3D bounding boxes using the depth information. Invalid object proposals can be further removed by analyzing...
Any large scale construction related activity generally requires the use of cranes. A crane operator must be appropriately skilled to avoid any mishap at the construction site. This can be accomplished by training crane operators on all the safety procedures and methods of crane operation to be practiced. In this paper we explore a method whereby anyone who is being trained as a crane operator, must...
Many state of the art object classification applications require many data samples, whose collection is usually a very costly process. Performing initial model training with synthetic samples (from virtual reality tools) has been proposed as a possible solution, although the resulting classification models need to be adapted (fine-tuned) to real-world data afterwards. For this bootstrapping process,...
Serious games have been used for several years in order to offer continuous and professional training to the companies employees. These games have unevenly affected different fields, they are less present in certain areas (industry) than others (medical, service, …) because of inherent specificity. In this article, we propose an approach to facilitate the implementation of a playful scenario dedicated...
Travel independently is one of the core skills required for children with intellectual disability to lead an independent life. Virtual reality based travel training system with natural interaction could help them to practice their travel skill in a safe environment without supervision. Developing real-time travel training system is a challenging work due to inherent complexity of 3D traffic simulation...
In this paper, based on the virtual scene images generated by the Unity3D engine, a target tracking realization method in UAV(Unmanned Aerial Vehicle) simulation training system is proposed. To realize the target tracking steadily, the LOS(line of sight) tracking model utilizing the target pixel offset in the consecutive frame image and the velocity tracking model are established. Meanwhile, a digital...
In this paper, we proposed a new 3D face reconstruction approach to reconstruct the 3D face from a single 2D image with arbitrary pose. The proposed approach enhanced the 3D morphable model by introducing a new local face shape constraint in another space. Then, the face can be constrained in double spaces: the global face shape space and the local face structure space. The advantages of the proposed...
Human 3D pose estimation from a single image is a challenging task with numerous applications. Convolutional Neural Networks (CNNs) have recently achieved superior performance on the task of 2D pose estimation from a single image, by training on images with 2D annotations collected by crowd sourcing. This suggests that similar success could be achieved for direct estimation of 3D poses. However, 3D...
This paper presents a method for 6D pose estimation from a single RGB image for complex texture-less objects. This class of objects are common in any environment but still challenging to deal with. This is due to the fact that the distribution of surface brightness makes difficult to compute interest points or appearance-based descriptors. Here we propose a novel part-based method using an efficient...
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