Humans show high-level of abstraction capabilities in games that require quickly communicating object information. They decompose the message content into multiple parts and communicate them an interpretable protocol. Toward equipping machines with such capabilities, we propose Primitive-based Sketch Abstraction task where goal is to represent sketches using a fixed set drawing primitives under...

Current feature-based methods for sketch recognition systems rely on human-selected features. Certain machine learning techniques have been found to be good nonlinear features extractors. In this paper, we apply a manifold learning method, kernel Isomap, with a new algorithm for multi-stroke sketch recognition, which significantly outperforms the standard featurebased techniques. INTRODUCTION S...

We explore the possibility of deeper linguistic research based on corpus and computational linguistic tools in this paper. In particular, we adopt Chinese Word Sketch, the application of Word Sketch Engine to Chinese GigaWord Corpus, for linguistic research. We apply Chinese Sketch Engine results to deeper linguistic account such as selectional restriction and event type selection. The study is...

Recommender systems utilize information retrieval and machine learning techniques for filtering information and can predict whether a user would like an unseen item. User similarity measurement plays an important role in collaborative filtering based recommender systems. In order to improve accuracy of traditional user based collaborative filtering techniques under new user cold-start problem a...

Simple and fast methods for transforming color photographs into non-photorealistic images such as stained-glass and color-sketch images. We propose two types of methods decomposing images into homogeneous color regions. One type is an edge-based method and the other is a region-based approach. In the edge-based methods, an input image is tessellated into Apollonius cells by using the distance t...

Distance Geometry puts the concept of distance at its center. The basic problem in distance geometry could be described as drawing an edge-weighted undirected graph in R for some given K such that the positions for adjacent vertices have distance which is equal to the corresponding edge weight. As we are unaware of any work in this field using any other norm but `2, we move some first steps usi...

The automatic recognition of facial expression presents a significant challenge to the pattern analysis and man-machine interaction research community. In this paper, a novel system is proposed to recognize human facial expressions based on the expression sketch. Firstly, facial expression sketch is extracted by an GPU-based real-time edge detection and sharpening algorithm from original gray i...

Due to the inaccuracy and noisy, uncertainty is inherent in time series streams, and increases the complexity of streams clustering. For the continuous arriving and massive data size, efficient data storage is a crucial task for clustering uncertain data streams. With hash-compressed structure, an extended uncertain sketch and update strategy are proposed to store uncertain data streams. And ba...

In this paper, we propose a method for creating freeform surfaces from sketch-annotated images. Beginning from an image, the user sketches object boundaries, features, and holes. Sketching is made easier by a magnetic pen that follows strong edges in the image. To create a surface from the sketch, a planar mesh is constructed such that its geometry aligns with the boundary and interior features...

Deep learning has been proven be very effective for various image recognition tasks, e.g., image classification, semantic segmentation, image retrieval, shape classification etc. However, existing works on deep learning for image recognition mainly focus on either natural image data or binary shape data. In this paper, we show that deep convolutional neural networks (DCNN) is also suitable for ...