Reprint of: Multi-scale 2D tracking of articulated objects using hierarchical spring systems

This paper presents a flexible framework to build a target-specific, part-based representation for arbitrary articulated or rigid objects. The aim is to successfully track the target object in 2D, through multiple scales and occlusions. This is realized by employing a hierarchical, iterative optimization process on the proposed representation of structure and appearance. Therefore, each rigid part of an object is described by a hierarchical spring system represented by an attributed graph pyramid. Hierarchical spring systems encode the spatial relationships of the features (attributes of the graph pyramid) describing the parts and enforce them by spring-like behavior during tracking. Articulation points connecting the parts of the object allow to transfer position information from reliable to ambiguous parts. Tracking is done in an iterative process by combining the hypotheses of simple trackers with the hypotheses extracted from the hierarchical spring systems.     

Markerless human articulated tracking using hierarchical particle swarm optimisation

In this paper, we address markerless full-body articulated human motion tracking from multi-view video sequences acquired in a studio environment. The tracking is formulated as a multi-dimensional non-linear optimisation and solved using particle swarm optimisation (PSO), a swarm-intelligence algorithm which has gained popularity in recent years due to its ability to solve difficult non-linear optimisation problems. We show that a small number of particles achieves accuracy levels comparable with several recent algorithms. PSO initialises automatically, does not need a sequence-specific motion model and recovers from temporary tracking divergence through the use of a powerful hierarchical search algorithm (HPSO). We compare experimentally HPSO with particle filter (PF), annealed particle filter (APF) and partitioned sampling annealed particle filter (PSAPF) using the computational framework provided by Balan et al. HPSO accuracy and consistency are better than PF and compare favourably with those of APF and PSAPF, outperforming it in sequences with sudden and fast motion. We also report an extensive experimental study of HPSO over ranges of values of its parameters.     

Joint origin identification of articulated robots with marker-based multi-camera optical tracking systems

Marker-based multi-camera optical tracking systems are being used in the robotics field to track robots for validation, verification, and calibration of their kinematic and dynamic models. These tracking systems estimate the pose of tracking bodies attached to objects within a tracking volume. In this work, we explore the case of tracking the origins of joints of articulated robots when the tracking bodies are mounted on limbs or structures relative to the joints. This configuration leads to an unknown relative pose between the tracking body and the joint origin. The identification of this relative pose is essential for an accurate representation of the kinematic model. We propose an approach for the identification of the origin of joints relative to tracking bodies by using state-of-the-art center of rotation (CoR) and axis of rotation (AoR) estimation methods. The applicability and effectiveness of our approach is demonstrated in two successful case studies: (i) the verification of the upper body kinematics of DLR’s humanoid Rollin’ Justin and (ii) the identification of the kinematic parameters of an ST Robot arm relative to its environment for the embodiment of a situated conversational assistant.     

基于三维视觉系统的多运动目标跟踪方法综述

多运动目标跟踪是智能视觉监控系统中的关键性的亟待解决的问题,采用二维视觉特征跟踪会在目标相互遮挡时丢失目标特征造成跟踪困难,近年来三维视觉跟踪系统越来越成为热点,利用三维特征能在多目标相互遮挡时更好地识别、跟踪目标,实现多目标遮挡时的精确跟踪,从而全面提高智能视觉监控系统的精确性。总结了近年来基于三维视觉系统的多运动目标跟踪方法,根据采用的不同三维视觉系统分为三类,将每类中具有代表性的方法进行了论述,分析了各典型方法的优缺点,最后提出了进一步研究的主要发展内容和趋势。     

Occlusion-aware multi-view reconstruction of articulated objects for manipulation

We present an algorithm called Procrustes-Lo-RANSAC (PLR) to recover complete 3D models of articulated objects. Structure-from-motion techniques are used to capture 3D point cloud models of an object in two different configurations. Procrustes analysis, combined with a locally optimized RANSAC sampling strategy, facilitates a straightforward geometric approach to recovering the joint axes, as well as classifying them automatically as either revolute or prismatic. With the resulting articulated model, a robotic system is then able to manipulate the object along its joint axes at a specified grasp point in order to exercise its degrees of freedom. Because the models capture all sides of the object, they are occlusion-aware, meaning that the robot has knowledge of parts of the object that are not visible in the current view. Our algorithm does not require prior knowledge of the object, nor does it make any assumptions about the planarity of the object or scene. Experiments with a PUMA 500 robotic arm demonstrate the effectiveness of the approach on a variety of real-world objects containing both revolute and prismatic joints.     

Human tracking using 3D surface colour distributions

A likelihood formulation for detailed human tracking in real-world scenes is presented. In this formulation, the appearance, modelled using feature distributions defined over regions on the surface of an articulated 3D model, is estimated and propagated as part of the state. The benefit of such a formulation over currently used techniques is that it provides a dense, highly discriminatory object-based cue that applies in real world scenes. Multi-dimensional histograms are used to represent the feature distributions and an on-line clustering algorithm, driven by prior knowledge of clothing structure, is derived that enhances appearance estimation and computational efficiency. An investigation of the likelihood model shows its profile to be smooth and broad while region grouping is shown to improve localisation and discrimination. These properties of the likelihood model ease pose estimation by allowing coarse, hierarchical sampling and local optimisation.     

3D reconstruction of free-formed line-like objects using NURBS representation

3D reconstruction of arbitrary free-formed objects is an important and challenging problem in computer vision. In this paper, we first discuss the importance of primitive selection in 3D reconstruction. Subsequently, a theorem, which reveals the perspective invariance of NURBS, is shown, making it a good choice as primitive in 3D reconstruction. Consequently, based on this theorem a new paradigm of free-formed line-like object reconstruction using NURBS as primitives is proposed. Furthermore, an approach for determining weights for 3D NURBS is presented, and the width effect of curved line-like objects is analyzed. Finally, experiments with line-like objects and machine part demonstrate the feasibility of our approach and prove the superiority of our approach over the point- or segment-based approaches as well as the B-spline-based reconstruction approach in terms of robustness and accuracy.     

Computing hierarchical curve-skeletons of 3D objects

A curve-skeleton of a 3D object is a stick-like figure or centerline representation of that object. It is used for diverse applications, including virtual colonoscopy and animation. In this paper, we introduce the concept of hierarchical curve-skeletons and describe a general and robust methodology that computes a family of increasingly detailed curve-skeletons. The algorithm is based upon computing a repulsive force field over a discretization of the 3D object and using topological characteristics of the resulting vector field, such as critical points and critical curves, to extract the curve-skeleton. We demonstrate this method on many different types of 3D objects (volumetric, polygonal and scattered point sets) and discuss various extensions of this approach.     

Real-time tracking of multiple objects in space-variant vision based on magnocellular visual pathway

In this paper, we propose a space-variant image representation model based on properties of magnocellular visual pathway, which perform motion analysis, in human retina. Then, we present an algorithm for the tracking of multiple objects in the proposed space-variant model. The proposed space-variant model has two effective image representations for object recognition and motion analysis, respectively. Each image representation is based on properties of two types of ganglion cell, which are the beginning of two basic visual pathways; one is parvocellular and the other is magnocellular. Through this model, we can get the efficient data reduction capability with no great loss of important information. And, the proposed multiple objects tracking method is restricted in space-variant image. Typically, an object-tracking algorithm consists of several processes such as detection, prediction, matching, and updating. In particular, the matching process plays an important role in multiple objects tracking. In traditional vision, the matching process is simple when the target objects are rigid. In space-variant vision, however, it is very complicated although the target is rigid, because there may be deformation of an object region in the space-variant coordinate system when the target moves to another position. Therefore, we propose a deformation formula in order to solve the matching problem in space-variant vision. By solving this problem, we can efficiently implement multiple objects tracking in space-variant vision.     

Optimal rotation alignment of 3D objects using a GPU-based similarity function

In this paper, we address the challenging task of finding the best alignment between two 3D objects by solving a global optimization problem in the space of rotations SO(3). The objective function to be optimized is a newly developed rotation-variant similarity measure, which is obtained directly from the object's geometry and is entirely implemented on the GPU. By exploiting the modern GPU's parallel architecture, we can process considerably greater amounts of data than a CPU implementation can do in the same amount of time. This allows us to create a similarity measure which combines speed and accuracy. The actual problem of rotation alignment is then solved by finding the global maximum of this similarity function in the space of rotations. A special rotation representation allows for an efficient local optimization on the manifold SO(3). Furthermore, unwanted local maxima can be avoided by a heuristic global optimization procedure which exploits rotational symmetry. Due to this common sense heuristics, the global search can be gradually reduced to a lower-dimensional problem up to a 1D line search to handle objects with high rotational symmetry. We show that our method is superior to existing normalization techniques such as PCA and provides a high degree of precision despite remarkably short runtimes.     

Efficient tracking of moving objects using a relational database

Tracking uncooperative moving objects by means of radar is a complex task due to clutter and association problems in multi-target scenarios. An approach to solve this problem is probabilistic multiple hypothesis tracking (PMHT). This method combines classical track filtering with a likelihood ratio test for the estimation of the plot-to-track association. The basics of PMHT and similar algorithms have gained much attention recently. However, the efficient implementation of real world applications of this technique still represents a challenging task. Since a common requirement in this context is the reliable storage of track data in a database, an implementation of the tracker's calculation inside a database management system (DBMS) using SQL views is desirable. A naive implementation of PMHT using a commercial DBMS, however, usually leads to performance problems because of the high frequency of measurement updates. In this paper, we propose possible optimizations for solving these performance problems. Their usage leads to a dramatic run-time improvement in our sample case and makes the implementation of PMHT in a database context feasible.     

Smooth control of an articulated mobile robot with switching constraints

The paper describes a smooth controller of an articulated mobile robot with switching constraints. The use of switching constraints associated with grounded/lifted wheels is an effective method of controlling various motions; e.g. the avoidance of a moving obstacle. A model of an articulated mobile robot that has active and passive wheels and active joints with switching constraints is derived. A controller that accomplishes the trajectory tracking of the robot’s head and subtasks using smooth joint input is proposed on the basis of the model. Simulations and experiments are presented to show the effectiveness of the proposed controller.     

基于全局最小化活动轮廓的多目标检测跟踪

为了在噪声干扰以及目标和背景颜色相近情况下实现多目标跟踪,提出一种基于快速全局最小化的活动轮廓模型的目标检测跟踪算法。该算法结合了基于边缘的活动轮廓模型和基于区域的活动轮廓模型,对能量泛函进行全局最小化来检测目标活动轮廓,用卡尔曼滤波预测目标下一帧的特征信息,然后用改进的最近邻法进行多目标跟踪。对图像序列的实验结果表明该算法能有效地对运动背景下多目标进行跟踪。     

Monocular 3D tracking of deformable surfaces using sequential second order cone programming

Reconstructing structures of deformable objects from monocular image sequences is important for applications like visual servoing and augmented reality. In this paper, we propose a method to recover 3D shapes of deformable surfaces using sequential second order cone programming (SOCP). The key of our approach is to represent the surface as a triangulated mesh and introduce two sets of constraints, one for model-to-image keypoint correspondences which are SOCP constraints, another for retaining the original lengths of the mesh edges which are non-convex constraints. In the process of tracking, the surface structure is iteratively updated by solving sequential SOCP feasibility problems in which the non-convex constraints are replaced by a set of convex constraints over a local convex region. The shape constraints used in our approach is more generic than previous methods, that enables us to reliably recover surface shapes with smooth, sharp and other complex deformations. The capability and efficiency of our approach are evaluated quantitatively with synthetic image sequences and qualitatively with real image sequences.     

二维线性连续系统稳定性的新判据

提出了一个检验二维线性连续系统稳定性的新算法。该算法基于多项式判别系统理论,可以对系统稳定与否作出完备的判断,克服了传统频域方法需要取大量频率点进行检验且只能提供近似结论的不足。更重要的是,此算法可以用于分析含参数系统的稳定裕度。实际案例显示了该算法的有效性。     

A new method for machining feature extracting of objects using 2D technical drawings

In this study, a new method called “3-Space” has been developed to obtain 3D models of prismatic machine parts using 2D technical drawings. This method uses 3 surfaces named Base, Top and Sweep Base for the determination of the objects. The edge colors have been given to the surfaces with meanings, and are used for the determination of the type and characteristics of the objects. 4 characteristics of the processing objects (namely external access direction, exit status, boundary geometry and the processing order of the features) have been determined. First, the object is considered a prismatic raw material, and the features to be processed on it are removed. Then the remaining object itself is created and thus a 3D view of the object is obtained.     

Unconstrained underwater multi-target tracking in passive sonar systems using two-stage PF-based technique

A robust particle filter (PF)-based multi-target tracking solution for passive sonar systems able to track an unknown time-varying number of multiple targets, while keeping continuous tracks of such targets, is presented in this article. PF is a nonlinear filtering technique that can accommodate arbitrary sensor characteristics, motion dynamics and noise distributions. An enhanced version of PF is employed and is called Mixture PF. The commonly used sampling/importance resampling PF samples from the prior importance density, while Mixture PF samples from both the prior and the observation likelihood. In order to be able to track an unknown time-varying number of multiple targets, two Mixture PFs are used, one for target detection and the other for tracking multiple targets, and a density-based clustering technique is used after the first filter. This article demonstrates the applicability of the proposed technique for the passive problem, which suffers from the lack of measurements and the small detection range of the buoys, especially for weak signals. A contact-level simulation was used to generate different scenarios and the performance of the proposed technique called Clustered-Mixture PF was examined with either bearing measurement only or bearing and Doppler measurements, and it demonstrated its high performance.     

一类分层非结构化P2P系统的随机切换模型

对于一类利用集中式构架和分布式构架各自优点的分层非结构化P2P系统,通过定义一种Markov切换空间模型来描述其动态分组切换行为.在Markov决策过程理论的基础上,给出了关于性能指标的策略迭代和在线策略迭代算法,并通过实例仿真说明该方法的优越性.     

Calibration of 3D kinematic systems using orthogonality constraints

Processing images acquired by multi-camera systems is nowadays an effective and convenient way of performing 3D reconstruction. The basic output, i.e. the 3D location of points, can easily be further processed to also acquire information about additional kinematic data: velocity and acceleration. Hence, many such reconstruction systems are referred to as 3D kinematic systems and are very broadly used, among other tasks, for human motion analysis. A prerequisite for the actual reconstruction of the unknown points is the calibration of the multi-camera system. At present, many popular 3D kinematic systems offer so-called wand calibration, using a rigid bar with attached markers, which is from the end user’s point of view preferred over many traditional methods. During this work a brief criticism on different calibration strategies is given and typical calibration approaches for 3D kinematic systems are explained. In addition, alternative ways of calibration are proposed, especially for the initialization stage. More specifically, the proposed methods rely not only on the enforcement of known distances between markers, but also on the orthogonality of two or three rigidly linked wands. Besides, the proposed ideas utilize common present calibration tools and shorten the typical calibration procedure. The obtained reconstruction accuracy is quite comparable with that obtained by commercial 3D kinematic systems.