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The perceived distance estimation in an immersive virtual reality system is generally underestimated to the actual distance. Approaches had been found to provide users with better dimensional perception. One method used in head-mounted displays is to interact by walking with visual feedback, but it is not suitable for a CAVE-like system, like imseCAVE, with confined spaces for walking. A verbal corrective...
We present a method for focal distance estimation of a freely-orienting eye using Purkinje-Sanson (PS) images, which are reflections of light on the inner structures of the eye. Using an infrared camera with a rigidly-fixed LED, our method creates an estimation model based on 3D gaze and the distance between reflections in the PS images that occur on the corneal surface and anterior surface of the...
1,000 fps motion vector (MV) estimation and classification engine for highspeed computational imaging in a 3D stacked imager/processor module is proposed, prototyped, assembled, and also tested. The module features 1) ThruChip interfaces for high fps image transfer, 2) orders of magnitude more area/power efficient MV estimation architecture compared to conventional ones, and 3) a cognitive classification...
Many current LIDAR systems generate huge amounts of 3D points, therefore efficient and fast data processing is essential. In urban areas surfaces are often planar and plane patches are an efficient representation for localization purposes. Our approach thus stores the points in a voxel grid and afterwards extracts the dominant plane using RANSACbased plane fitting. Classical RANSAC-based plane extraction...
This paper presents a model based approach for the real-time estimation of a gaseous plume using a time-varying formation of unmanned aerial vehicles (UAVs). Such a dynamic formation is necessitated by sensor technology limitations that can only obtain concentration measurements and not spatial gradients of concentration. It is assumed that gas is released in the atmosphere by a stationary or a moving...
In this paper we present a novel approach for 3D facial expression recognition based on a registration method. The used registration method, called the Coherent Point Drift (CPD), is applied to estimate complex non-linear and nonrigid transformation between 3D facial surfaces. The computed transformation allows to recover shape deformations that are induced by facial expression variations. Machine...
Depth estimation and spatial awareness given a single monocular image is a challenging task for a computer as depth information is not retained when the 3D world is projected onto a 2D plane. Therefore, we must combine our prior knowledge with other monocular cues present in the image, such as occlusion, texture variations, and shadows to understand the depth of the image. In this paper, we present...
In this paper, we address the 3D eye gaze estimation problem using a low-cost, simple-setup, and non-intrusive consumer depth sensor (Kinect sensor). We present an effective and accurate method based on 3D eye model to estimate the point of gaze of a subject with the tolerance of free head movement. To determine the parameters involved in the proposed eye model, we propose i) an improved convolution-based...
3D LiDAR is widely used for mobile robots environment perception nowadays, which has high precision of distance measurement. In this paper, a calibration method which is suitable for Velodyne VLP-16 is firstly introduced. And then we utilize statistical filtering for isolated points removal. After statistical filtering, a slope location and orientation estimation method is presented based on PROSAC...
As a fundamental problem in computer vision community, non-rigid point set registration is a challenging topic since the corresponding transformation model is often unknown and difficult to model. In this paper, we present a robust method for non-rigid point set registration. Firstly, a mixture of asymmetric Gaussian model (MoAG) is employed to capture spatially asymmetric distributions which the...
In this paper, we propose a new feature-point based RGB-D visual odometry approach for estimating the relative camera motion from two consecutive frames. The approach differs from most feature-point based RGB-D visual odometry approaches in two key aspects: (1) we do not directly use point correspondences to compute relative motion, instead, we link each two distinct points to form a line segment,...
Light field cameras capture a scene's multi-directional light field with one image, allowing the estimation of depth. In this paper, we introduce a fully automatic method for depth estimation from a single plenoptic image running a RANSAC-like algorithm for feature matching. The novelty about our method is the global method to back project correspondences found using photometric similarity to obtain...
A new camera calibration approach is proposed that can utilize the affine transformations and surface normals of small spatial patches. Even though classical calibration algorithms use only point locations, images contain more information than simple 2D point coordinates. New methods are presented in this paper for the calibration problem with their closed-form solutions, then the estimated parameters...
The ubiquitous hand gesture plays an important role in the natural human machine interaction (HMI). Recently, the consumer color and depth cameras have been used to estimate hand shapes and postures for the mid-air HMI. Under the observation that 3D hand contours possess much information of hand postures, we estimate 3D hand contours from infrared images with a limited computation complexity for the...
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...
Developing reliable and robust face verification systems has been a tough challenge in computer vision, for several decades. The variation in illumination and head pose may seriously inhibit the accuracy of two-dimensional face recognition. With the invention of a depth map sensor, more three-dimensional volume data can be processed to mitigate the problem associated with face verification. This paper...
The absolute orientation problem arises often in vision and robotics. Despite that robust algorithmic solutions exist for quite some time, they all rely on matrix factorizations such as eigen or singular value decomposition. These factorizations are relatively expensive to compute, therefore might become a performance bottleneck when absolute orientation needs to be repeatedly computed on low-end...
Recently LiDAR-camera systems have rapidly emerged in many applications. The integration of laser range-finding technologies into existing vision systems enables a more comprehensive understanding of 3D structure of the environment. The advantage, however, relies on a good geometrical calibration between the LiDAR and the image sensors. In this paper we consider visual odometry, a discipline in computer...
When a planar structure is observed from multiple views, the projections of its corresponding 3D points on each image are related by a homography. Its estimation is a key step in many computer vision tasks where either the rigid motion between views or a per-pixel image correspondence is sought. The vast majority of multi-view homography estimation techniques relies on matching a sparse set of point-to-point...
Traditional gaze tracking systems rely on explicit infrared lights and high resolution cameras to achieve high performance and robustness. These systems, however, require complex setup and thus are restricted in lab research and hard to apply in practice. In this paper, we propose to perform gaze tracking with a consumer level depth sensor (Kinect). Leveraging on Kinect's capability to obtain 3D coordinates,...
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