In biology, the morphometric analysis is widely used to analyze the inter-organisms variations. It allows to classify and to determine the evolution of an organism’s family. The morphometric methods consider features such as shape, structure, color, or size of the studied objects. In previous works [8], we have analyzed beetle mandibles by using the centroid as feature, in order to classify the beetles. We have shown that the Probabilistic Hough Transform (PHT) is an efficient unsupervised method to compute the centroid. This paper proposes a new approach to precisely estimate the landmark geometry, points of interest defined by biologists on the mandible contours. In order to automatically register the landmarks on different mandibles, we defined patches around manual landmarks of the reference image. Each patch is described by computing its SIFT descriptor. Considering a query image, we apply a registration step performed by an Iterative Principal Component Analysis which identify the rotation and translation parameters. Then, the patches in the query image are identified and the SIFT descriptors computed. The biologists have collected 293 beetles to provide two sets of mandible images separated into left and right side. The experiments show that, depending on the position of the landmarks on the mandible contour, the performance can go up to 98% of good detection. The complete workflow is implemented in the MAELab framework, freely available as library on GitHub.
It is well known that multi-sensory stimulation can enhance immersion within virtual environments. Whilst there has been rapid development of devices which can enhance the visual immersion, technology to stimulate other senses, such as touch, is still under developed. Currently there is a problem wherein a surface in a virtual environment, such as a wall, cannot replicate the physical properties of a solid object. In this paper a novel system is proposed utilising the HTC VIVE and Rethink Robotics' Baxter Robot to replicate surfaces. A demonstration has been created whereby a user climbs a wall in a virtual environment by grabbing onto ledges which exist as a physical body located on Baxter's end effector. The system uses bi-directional TCP communication between an environment developed in Epic Games' Unreal Engine and the Baxter robot running the Robot Operating System framework. When an ascending user reaches out and grabs a ledge on the virtual wall they will be applying a torque to the Baxter arm which can be measured and the intended movement of the user inferred, resulting in the ledge being moved through a suitable Inverse Kinematics path. This has provided the user with the ability to climb a wall in VR in the absence of any hand tracking methods whilst receiving force feedback from the ledges they grasp onto. Current alternative systems only exist as wearables or operate in small spaces. The increased immersion in this VR demo can be used to assist those with phobias of heights.
With the release of various low cost consumer head mounted displays, such as the HTC Vive, virtual reality (VR) visualisation technology is becoming common place. However, haptic interactions continue to lag behind the visual developments. Touch feedback from the HTC Vive system is only provided by way of vibrations in the physical controllers. There are currently no large scale haptic devices that allow a user to experience force feedback in a room scale VR environment. The research presented in this paper demonstrates this problem can be addressed through the use of a large robotic arm to create an encounter haptic solution. Our haptic VR system uses the HTC Vive and the Baxter robot. Positional data is taken from the Vive controllers and sent to one of the Baxter's 7 degrees of freedom arms, which is used to provide force feedback to the user. An experiment was created where a user pushes wooden boxes off a wall in a VR environment. Several tests were performed. Different virtual boxes with a different simulated weight were simulated by varying the speed at which the Baxter moves away from the user. Results from a thirty participant user study indicate that desirable haptic effects can be achieved in a large room scale environment.
This paper presents an efficient algorithm for a global parameterization of triangular surface meshes. In contrast to previous techniques which achieve global parameterization through the optimization of non-linear systems of equations, our algorithm is solely based on solving at most two linear equation systems, in the least square sense. Therefore, in terms of running time the unfolding procedure is highly efficient. Our approach is direct – it solves for the planar UV coordinates of each vertex directly – hence avoiding any numerically challenging planar reconstruction in a post-process. This results in a robust unfolding algorithm. Curvature prescription for user-provided cone singularities can either be specified manually, or suggested automatically by our approach. Experiments on a variety of surface meshes demonstrate the runtime efficiency of our algorithm and the quality of its unfolding. To demonstrate the utility and versatility of our approach, we apply it to seamless texturing. The proposed algorithm is computationally efficient, robust and results in a parameterization with acceptable metric distortion.
Image deformation technique is widely used in the field of computer animation, image editing, medical imaging, and other applications in 2D and 3D computer graphics. All the algorithms aim to provide simple user interface, most of which need the user to drag the control points, lines or polygon. The deformation process and the final position of the controlling points should be smooth and precise respectively, and it should also run in real-time.This paper provides a simple image deformation method using the radial basis function interpolation in approximation theory. Radial basis function is a very popular and convenient tool for data representation problems. The proposed method using radial basis function is fast and easy to use more than previous deformation methods. Experiments indicate that the algorithm is stable and well performed.
