Semantic Object Parsing with Graph LSTM

By taking the semantic object parsing task as an exemplar application scenario, we propose the Graph Long Short-Term Memory (Graph LSTM) network, which is the generalization of LSTM from sequential data or multi-dimensional data to general graph-structured data. Particularly, instead of evenly and fixedly dividing an image to pixels or patches in existing multi-dimensional LSTM structures (e.g., Row, Grid and Diagonal LSTMs), we take each arbitrary-shaped superpixel as a semantically consistent node, and adaptively construct an undirected graph for each image, where the spatial relations of the superpixels are naturally used as edges. Constructed on such an adaptive graph topology, the Graph LSTM is more naturally aligned with the visual patterns in the image (e.g., object boundaries or appearance similarities) and provides a more economical information propagation route. Furthermore, for each optimization step over Graph LSTM, we propose to use a confidence-driven scheme to update the hidden and memory states of nodes progressively till all nodes are updated. In addition, for each node, the forgets gates are adaptively learned to capture different degrees of semantic correlation with neighboring nodes. Comprehensive evaluations on four diverse semantic object parsing datasets well demonstrate the significant superiority of our Graph LSTM over other state-of-the-art solutions.Comment: 18 page

Deep Vectorization of Technical Drawings

We present a new method for vectorization of technical line drawings, such as floor plans, architectural drawings, and 2D CAD images. Our method includes (1) a deep learning-based cleaning stage to eliminate the background and imperfections in the image and fill in missing parts, (2) a transformer-based network to estimate vector primitives, and (3) optimization procedure to obtain the final primitive configurations. We train the networks on synthetic data, renderings of vector line drawings, and manually vectorized scans of line drawings. Our method quantitatively and qualitatively outperforms a number of existing techniques on a collection of representative technical drawings

Motion Synthesis of a Planar Watt II Type Six-Bar Mechanism with Two End-Effectors

The study deals with motion generation with closed-loop mechanisms with several end-effectors. As a case study a single degree-of-freedom planar Watt II type six-bar mechanism with two end-effectors is worked on. Dyad formulation with complex numbers is made use of for the mathematical model. It is found that the motion synthesis is possible for at most three poses of the two end-effectors. The formulations are illustrated with numerical examples

Integer‐Grid Sketch Simplification and Vectorization

International audienceA major challenge in line drawing vectorization is segmenting the input bitmap into separate curves. This segmentation is especially problematic for rough sketches, where curves are depicted using multiple overdrawn strokes. Inspired by feature-aligned mesh quadrangulation methods in geometry processing, we propose to extract vector curve networks by parametrizing the image with local drawing-aligned integer grids. The regular structure of the grid facilitates the extraction of clean line junctions; due to the grid's discrete nature, nearby strokes are implicitly grouped together. We demonstrate that our method successfully vectorizes both clean and rough line drawings, whereas previous methods focused on only one of those drawing types

Solvable Multi-Fingered Hands for Exact Kinematic Synthesis

Multi-fingered hands are kinematic chains with a tree topology, that is, with a set of common joints that span several branches and end-effectors. When performing dimensional kinematic synthesis with simultaneous tasks for all the end-effectors, a new solvability criterion needs to be applied that includes checking the solvability of sub-chains. This criterion yields as a result that not all possible topologies are solvable for a common number of positions for all end-effectors. This article shows and proves the solvability criterion and derives some properties of the kinematic chains with tree topology for a single branching and identical fingersPeer ReviewedPostprint (published version

Verksamhetsmodell för klinisk specialistsjukskötare inom samjour vid Vasa centralsjukhus : - en kvalitativ studie

Syftet med studien var att utveckla en verksamhetsmodell för klinisk specialistsjukskötare inom samjour vid Vasa centralsjukhus. Frågeställningen för studien var: Hur skall verksamhetsmodellen utformas för en klinisk specialistsjukskötare? Vilka ansvarsområden kan en klinisk specialistsjukskötare inneha vid samjouren? Vilka arbetsuppgifter kan en klinisk specialistsjukskötare ha inom samjouren vid Vasa centralsjukhus? Metoden som användes var aktionsforskning med kvalitativ ansats. Datainsamlingsmetoden var enkät med öppna frågor till klinisk specialistsjukskötare i expertfunktion inom specialsjukvården och inom primärhälsovården vid olika sjukvårdsdistrikt i Finland. Data analyserades med innehållsanalys. För att utvärdera verksamhetsmodellen användes enkätsvaren och forskningar. Utgående från svaren bearbetades verksamhetsmodellen till det slutliga formatet. Resultatet av studien visar att klinisk specialistsjukskötaren arbetar självständigt, innehar en fördjupad medicinsk kompetens och har ett ansvar för att patienten skall få en evidensbaserad vård. Resultatet i studien visar också att om en klinisk specialistsjukskötare implementeras inom organisationen så utvecklas verksamhetsmodeller enligt de internationella kraven. Verksamhetsmodellens tyngdpunkt sätts på en god och trygg vård till patienterna. Målgruppen för klinisk specialistsjukskötare i denhär studien är främst patienter som besöker samjouren vid Vasa centralsjukhus.The aim of the study was to develop a case of management model for a clinical nurse specialist in primary health care at Vaasa Central Hospital. The research question was the following: How will the operational model be designed for a clinical nurse specialist? What responsibilities can be given to clinical nurse specialists in primary health care? What duties can clinical nurse specialists have within primary health care at Vaasa Central Hospital? The method used was action research with a qualitative approach. The instrument was a questionnaire with open-ended questions for nurses performing expert duties within specialist health care and primary health care, in various medical care districts in Finland. The data was analysed by means of content analysis. In order to evaluate the management model, the questionnaire responses and previous research were used, and based on the responses the management model was developed into its final format. The results of the study show that the clinical nurse specialist works independently, possesses in-depth medical skills and has a responsibility to ensure that the patient receives evidence-based care. The results of the study also show that the clinical nurse specialist is implemented within the organization to develop management models with the international requirements. The emphasis of the management model is good and safe care for patients. The target group for the clinical nurse specialist in this study is primarily patients who visit the primary health care at Vaasa Central Hospital

Structural Synthesis of Hands for Grasping and Manipulation Tasks

In the kinematic synthesis of multi-fingered robotic hands for a specific task, the selection of the hand topology is an important step. Considerable research efforts have been directed to the structural synthesis of hand topologies for satisfying grasping and manipulation metrics such as mobility and force closure. In this work, we develop a structural synthesis, isomorphism-free enumeration method that combines the solvability for rigid-body guidance with the grasping and manipulation metrics, for general hands with a tree structure. An algorithmic implementation of the methodology is presented and illustrated with validation examples.Peer ReviewedPostprint (author's final draft

Contributions to rotation invariant character recognition

Optical character recognition of machine-and hand-written numeral images has been improved by new methods for the rotation and translation invariant recognition of images using the rotation-invariant properties of an othogonal two-dimensional transform, the Zernike transform. Two algorithms for the estimation of the rotation invariant coefficient magnitude have been developed and tested. In addition, a new rotation normalisation procedure is presented, which performs a rotation of the image into a standard position. In the case of machine-written digits, the magnitudes of the Zernike coefficients are used as features, and classification is performed with the Condensed Nearest Neighbour Network. For hand-written digits the rotation normalisation procedure is applied, and images are classified with a Multilayer Perceptron resulting in a recognition rate of 96 %. (WEN)Available from TIB Hannover: RR 4652(8) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Fully-Convolutional Siamese Networks for Object Tracking

The problem of arbitrary object tracking has traditionally been tackled by learning a model of the object’s appearance exclusively online, using as sole training data the video itself. Despite the success of these methods, their online-only approach inherently limits the richness of the model they can learn. Recently, several attempts have been made to exploit the expressive power of deep convolutional networks. However, when the object to track is not known beforehand, it is necessary to perform Stochastic Gradient Descent online to adapt the weights of the network, severely compromising the speed of the system. In this paper we equip a basic tracking algorithm with a novel fully-convolutional Siamese network trained end-to-end on the ILSVRC15 dataset for object detection in video. Our tracker operates at frame-rates beyond real-time and, despite its extreme simplicity, achieves state-of-the-art performance in multiple benchmarks