FMS实时控制系统动态建模方法(一)

在建立FMS物理对象的功能模型，状态转移图（STD），面向对象的Petri网（OPN）模型的基础上，本文将着色Petri网与面向对象技术相结合，提出了一种实时控制系统的建模方法－面向对象的着色Petri网（OCPN）建模方法，此建模方法在无锡职业学院的FMS的实时控制系统中得到验证。     

Automatic annotation of tennis games: An integration of audio,vision, and learning

Fully automatic annotation of tennis game using broadcast video is a task with a great potential but with enormous challenges. In this paper we describe our approach to this task, which integrates computer vision, machine listening, and machine learning. At the low level processing, we improve upon our previously proposed state-of-the-art tennis ball tracking algorithm and employ audio signal processing techniques to detect key events and construct features for classifying the events. At high level analysis, we model event classification as a sequence labelling problem, and investigate four machine learning techniques using simulated event sequences. Finally, we evaluate our proposed approach on three real world tennis games, and discuss the interplay between audio, vision and learning. To the best of our knowledge, our system is the only one that can annotate tennis game at such a detailed level.     

Validating an object placement planner for robotic pick-and-place tasks

This paper proposes an object placement planner for a grasped object during pick-and-place tasks. The proposed planner automatically determines the pose of an object that is stably placed near a user-assigned point on the environment surface. In our proposed method, first the polygon models of both the object and the environment are clustered, with each cluster being approximated by a planar region. The position/orientation of an object placed on the environment surface can be determined by selecting a pair of clusters: one from the object and the other from the environment. We furthermore conduct several tests to determine the position/orientation of the object, namely the Convexity Test, the Contact Test and the Stability Test. We demonstrate that, by using the polygon model of the environment that is obtained by means of conversion of the point cloud, we can determine the position/orientation of an object and can thereby realize a pick-and-place task.     

基于Android的会议终端

为满足会议系统对设备小型、智能、方便运输、易于拓展的要求,设计并实现了一种基于Android的会议终端。终端采用可扩展标记语言（ XML）文件定义用户界面,实现界面逻辑与业务逻辑分离,具有很强的自适应性;采用跨平台的Socket通信方式和JSON数据交换语言与服务器进行通信,并结合使用UDP和TCP协议,实现了终端与服务器的松耦合;终端设置项少,无须录入会议内容,简化了用户操作;利用Android内置的SQLite数据库保存会议信息和结果,使数据管理简单高效。阐述了终端的整体设计,给出了终端程序的模块划分和流程。实验表明,终端工作流畅稳定,运行无明显延时,可以为现代会议提供优质的服务。     

Coupling-and-decoupling: A hierarchical model for occlusion-free object detection

Handling occlusion is a very challenging problem in object detection. This paper presents a method of learning a hierarchical model for X-to-X occlusion-free object detection (e.g., car-to-car and person-to-person occlusions in our experiments). The proposed method is motivated by an intuitive coupling-and-decoupling strategy. In the learning stage, the pair of occluding X?s (e.g., car pairs or person pairs) is represented directly and jointly by a hierarchical And–Or directed acyclic graph (AOG) which accounts for the statistically significant co-occurrence (i.e., coupling). The structure and the parameters of the AOG are learned using the latent structural SVM (LSSVM) framework. In detection, a dynamic programming (DP) algorithm is utilized to find the best parse trees for all sliding windows with detection scores being greater than the learned threshold. Then, the two single X?s are decoupled from the declared detections of X-to-X occluding pairs together with some non-maximum suppression (NMS) post-processing. In experiments, our method is tested on both a roadside-car dataset collected by ourselves (which will be released with this paper) and two public person datasets, the MPII-2Person dataset and the TUD-Crossing dataset. Our method is compared with state-of-the-art deformable part-based methods, and obtains comparable or better detection performance.     

Predictive models for multibiometric systems

Recognizing a subject given a set of biometrics is a fundamental pattern recognition problem. This paper builds novel statistical models for multibiometric systems using geometric and multinomial distributions. These models are generic as they are only based on the similarity scores produced by a recognition system. They predict the bounds on the range of indices within which a test subject is likely to be present in a sorted set of similarity scores. These bounds are then used in the multibiometric recognition system to predict a smaller subset of subjects from the database as probable candidates for a given test subject. Experimental results show that the proposed models enhance the recognition rate beyond the underlying matching algorithms for multiple face views, fingerprints, palm prints, irises and their combinations.     

Inverse Procedural Modelling of Trees

Procedural tree models have been popular in computer graphics for their ability to generate a variety of output trees from a set of input parameters and to simulate plant interaction with the environment for a realistic placement of trees in virtual scenes. However, defining such models and their parameters is a difficult task. We propose an inverse modelling approach for stochastic trees that takes polygonal tree models as input and estimates the parameters of a procedural model so that it produces trees similar to the input. Our framework is based on a novel parametric model for tree generation and uses Monte Carlo Markov Chains to find the optimal set of parameters. We demonstrate our approach on a variety of input models obtained from different sources, such as interactive modelling systems, reconstructed scans of real trees and developmental models.     

Sets of Globally Optimal Stream Surfaces for Flow Visualization

Stream surfaces are a well‐studied and widely used tool for the visualization of 3D flow fields. Usually, stream surface seeding is carried out manually in time‐consuming trial and error procedures. Only recently automatic selection methods were proposed. Local methods support the selection of a set of stream surfaces, but, contrary to global selection methods, they evaluate only the quality of the seeding lines but not the quality of the whole stream surfaces. Global methods, on the other hand, only support the selection of a single optimal stream surface until now. However, for certain flow fields a single stream surface is not sufficient to represent all flow features. In our work, we overcome this limitation by introducing a global selection technique for a set of stream surfaces. All selected surfaces optimize global stream surface quality measures and are guaranteed to be mutually distant, such that they can convey different flow features. Our approach is an efficient extension of the most recent global selection method for single stream surfaces. We illustrate its effectiveness on a number of analytical and simulated flow fields and analyze the quality of the results in a user study.     

Variational Tree Synthesis

Modelling trees according to desired shapes is important for many applications. Despite numerous methods having been proposed in tree modelling, it is still a non‐trivial task and challenging. In this paper, we present a new variational computing approach for generating realistic trees in specific shapes. Instead of directly modelling trees from symbolic rules, we formulate the tree modelling as an optimization process, in which a variational cost function is iteratively minimized. This cost function measures the difference between the guidance shape and the target tree crown. In addition, to faithfully capture the branch structure of trees, several botanical factors, including the minimum total branches volume and spatial branches patterns, are considered in the optimization to guide the tree modelling process. We demonstrate that our approach is applicable to generate trees with different shapes, from interactive design and complex polygonal meshes.     

A Projective Framework for Polyhedral Mesh Modelling

We present a novel framework for polyhedral mesh editing with face‐based projective maps that preserves planarity by definition. Such meshes are essential in the field of architectural design and rationalization. By using homogeneous coordinates to describe vertices, we can parametrize the entire shape space of planar‐preserving deformations with bilinear equations. The generality of this space allows for polyhedral geometric processing methods to be conducted with ease. We demonstrate its usefulness in planar‐quadrilateral mesh subdivision, a resulting multi‐resolution editing algorithm, and novel shape‐space exploration with prescribed transformations. Furthermore, we show that our shape space is a discretization of a continuous space of conjugate‐preserving projective transformation fields on surfaces. Our shape space directly addresses planar‐quad meshes, on which we put a focus, and we further show that our framework naturally extends to meshes with faces of more than four vertices as well.