Motion Graph Research Articles

A real-time system for motion retrieval and interpretation

This paper proposes a new examplar-based method for real-time human motion recognition using Motion Capture (MoCap) data. We have formalized streamed recognizable actions, coming from an online MoCap engine, into a motion graph that is similar to an animation motion graph. This graph is used as an automaton to recognize known actions as well as to add new ones. We have defined and used a spatio-temporal metric for similarity measurements to achieve more accurate feedbacks on classification. The proposed method has the advantage of being linear and incremental, making the recognition process very fast and the addition of a new action straightforward. Furthermore, actions can be recognized with a score even before they are fully completed. Thanks to the use of a skeleton-centric coordinate system, our recognition method has become view-invariant. We have successfully tested our action recognition method on both synthetic and real data. We have also compared our results with four state-of-the-art methods using three well known datasets for human action recognition. In particular, the comparisons have clearly shown the advantage of our method through better recognition rates.

Interactive Dynamic Background Scene Generator Based on Limited Input Motions

In this paper, an interactive dynamic background scene generating and editing system is proposed based on improved motion graph. By analyzing the input motions with limited frame length and their metadata, our system could synthesize a large amount of various motions to yield a composing dynamic background scene with unlimited frame length by connecting the motion pieces through smooth transitions based on their motion graph layers. The motion pieces are generated by segmenting the input motions and corresponding deforming meshes spatially and temporally, while the smooth transitions connected the motion pieces are obtained by searching the best path in the motion graph layers according to the specified circumstances. Finally, the result motions are optimized by repeatedly substituting the motion sub-sequences. To design the dynamic background scene, users can interactively specify some physical constraints of the environment on the keyframes, such as wind direction or velocity of flow, or even some simple paths for characters to follow, and the system can automatically generate a continuous and natural dynamic background scene in accordance with the user-specified environment constraints.

Guiding Explorations: Design Principles and Functions of Interactive Diagrams

As part of a long-term research project about the design of guided inquiry in mathematics classrooms, we studied the design principles and the functions of a specific class of interactive digital diagrams called narrating interactive diagrams. These diagrams are designed to provide a structure for the available options in explorations. They provide tools to promote inquiry, and at the same time set boundaries to guide the inquiry. They also provide a framework and narration of the story to be learned in the process of working on the task. The authors explore whether and how interactive diagrams centered upon an animation of multi-process motion and parallel time-position graphs guide students’ inquiry. To educators, who are challenged by the design and the implementation of interactive mathematics instructional materials, this study offers ways and terms to think about designs that limit the student's action and so support guidance, and at the same time remain an open space for student ideas.

Laplacian coordinates-based motion transition for data-driven motion synthesis

As a fundamental technique in data-driven (or example-based) methods, motion blending has been employed to produce new motion clip from two or more clips or introduced as a medium to improve the final result of other method, for example, motion graphs. As methods of motion blending always require the system or users to classify the motion samples, it is difficult to accomplish motion blending automatically and to preserve local details, such as angular accelerations of joints of original motions. In this study, the authors developed a framework based on Laplacian coordinates to produce transitions between two motion clips, emphasising on preserving local details, without any need of motion classification. At first, multidimensional Laplacian coordinates are introduced to present local details of joints' angle. Then an error function is deduced to measure how much result motions differ from original ones in local details. By minimising such error function, new motions can then finally generated, which can preserve local details of input motion clips as much as possible. The following experiments show the effectiveness of the authors' framework.

Continuous Full-Body Motion Control of Virtual Human Using Sparse Wiimotes

Sparse sensors that recognize full-body human motion and that control the motion of virtual humans have emerged as valuable research tools in the field of human–computer interactions. Here we propose a method for motion recognition and prolonged, continuous generation of motion data based on the recognition results. The only inputs required are the directional accelerations collected by four Wii remotes, which are attached on the four limbs of a human. The extended and continuous signal sequences are separated into small segments that can be described by particular motion content. Use of a fused hidden Markov model (FHMM) during the recognition process ensures the accuracy and efficiency with which independent motion segments are recognized. A graph model enhances the capacity of classification when dealing with a signal sequence associated with a prolonged motion. During the reconstruction and generation processes, an efficient state-based motion graph generates the extended and continuous virtual human motion data, which accurately reflects variation in the movement of the actors. Our method has a strong capacity to classify types of motion upon their recognition and the control process can be applied to a range of applications involving interaction.

13-5 ダンスの多様性向上のための拡張Motion Graphの生成(第13部門CGモデリング&レンダリング)

13-5 ダンスの多様性向上のための拡張Motion Graphの生成(第13部門CGモデリング&レンダリング)

Topology Dictionary for 3D Video Understanding

This paper presents a novel approach that achieves 3D video understanding. 3D video consists of a stream of 3D models of subjects in motion. The acquisition of long sequences requires large storage space (2 GB for 1 min). Moreover, it is tedious to browse data sets and extract meaningful information. We propose the topology dictionary to encode and describe 3D video content. The model consists of a topology-based shape descriptor dictionary which can be generated from either extracted patterns or training sequences. The model relies on 1) topology description and classification using Reeb graphs, and 2) a Markov motion graph to represent topology change states. We show that the use of Reeb graphs as the high-level topology descriptor is relevant. It allows the dictionary to automatically model complex sequences, whereas other strategies would require prior knowledge on the shape and topology of the captured subjects. Our approach serves to encode 3D video sequences, and can be applied for content-based description and summarization of 3D video sequences. Furthermore, topology class labeling during a learning process enables the system to perform content-based event recognition. Experiments were carried out on various 3D videos. We showcase an application for 3D video progressive summarization using the topology dictionary.

An improved approach to the efficient construction of and search operations in motion graphs

Motion graphs have been widely used as an effective technique in the synthesis of human motions. To synthesize well-formed motions, motion graphs require smooth transitions and good connectivity. However, the time and costs grow quadratically as the graph size increases. In this paper, we present a method to set up a hierarchical structure, called a structure table. The coarse level of this graph models different motion categories and their transitions, and the fine level mainly captures different motion styles. An interpolation space method is used to improve the graph connectivity at the fine level. This structure guides the establishment of a faster and more realistic graphical object. After the building process, this structure also helps with searching the motion graph, by performing a traverse search and placing the findings into a direct look-up table or local search depository. Moreover, when there is no direct link between the different motions, a navigation map is introduced to conduct an appropriate search path via a series of transition motion clips. The experimental results indicate that our approach could lower the computation time in construction and searching, while simultaneously providing a richer variety of motion styles.

Efficient Generation of Dancing Animation Synchronizing with Music Based on Meta Motion Graphs

Efficient Generation of Dancing Animation Synchronizing with Music Based on Meta Motion Graphs

5-5 Motion Graphを利用した自動生成ダンスの動きの多様性に関する検討(第5部門 CGモデリングとその応用)

5-5 Motion Graphを利用した自動生成ダンスの動きの多様性に関する検討(第5部門 CGモデリングとその応用)

Gaussian process motion graph models for smooth transitions among multiple actions

We propose a unified model for human motion prior with multiple actions. Our model is generated from sample pose sequences of the multiple actions, each of which is recorded from real human motion. The sample sequences are connected to each other by synthesizing a variety of possible transitions among the different actions. For kinematically-realistic transitions, our model integrates nonlinear probabilistic latent modeling of the samples and interpolation-based synthesis of the transition paths. While naive interpolation makes unexpected poses, our model rejects them (1) by searching for smooth and short transition paths by employing the good properties of the observation and latent spaces and (2) by avoiding using samples that unexpectedly synthesize the nonsmooth interpolation. The effectiveness of the model is demonstrated with real data and its application to human pose tracking.

Supporting Fourth Graders’ Ability to Interpret Graphs Through Real-Time Graphing Technology: A Preliminary Study

This study examined to what extent inquiry-based instruction supported with real-time graphing technology improves fourth grader’s ability to interpret graphs as representations of physical science concepts such as motion and temperature. This study also examined whether there is any difference between inquiry-based instruction supported with real-time graphing software and inquiry-based instruction supported with traditional laboratory equipment in terms of improving fourth graders’ ability to interpret motion and temperature graphs. Results of this study showed that there is a significant advantage in using real-time graphing technology to support fourth graders’ ability to interpret graphs.

Generation of Hypoid Gears on CNC Hypoid Generator

In this study, polynomial functions of orders up to five are applied to induce variations in the cradle radial setting and the velocity ratio in the kinematic scheme of the machine tool for the generation of the pinion tooth surfaces corresponding to reduced transmission error amplitudes of a hypoid gear pair. The new CNC hypoid generators have made it possible to perform this nonlinear correction motions for the cutting of the face-milled hypoid gears. An algorithm is developed for the execution of motions on the CNC hypoid generator for the generation of face-milled hypoid gear tooth surface, based on the machine tool setting variation on the cradle-type hypoid generator induced by the optimal polynomial functions up to fifth-order. By using the corresponding computer program, the motion graphs of the CNC hypoid generator are determined for the generation of hypoid gear tooth surface, based on the optimal variation in the velocity ratio in the kinematic scheme and on the variation in the cradle radial setting on a cradle-type generator. The results presented indicate that the variation of the velocity ratio in the kinematic scheme of the hypoid generator induced by a fifth-order polynomial function resulted in a 62% reduction of the maximum transmission error of the gear pair.

A Rapid Behavior Simulation Approach for Fishes

Simulating fish behavior is a typical application in artificial life studies. The traditional approaches are based on solving equations of mathematical physics. They are only able to simulate few fishes in real time. This motivates us to present a rapid approach capable of simulating fishes. Our approach adopts motion graph to represent the athletic ability of fish, and uses a path planning to simulate various behaviors based on the motion graph. Experiments show that this approach is very efficient and has great potential in simulating large-scale fish shoal.

Fast Motion Synthesis of Massive Number of Quadruped Animals

This paper presents a fast and practical motion synthesis algorithm for massive number of quadruped animals. The algorithm constructs so called speed maps that contain a set of same style motions but different speed from a single cyclic motion by using IK(Inverse Kinematics) solver. Then, those speed maps are connected each other to form a motion graph. At run time, given a point trajectory that obtained from user specification or simulators, the algorithm retrieves proper speed motions from the graph, and modifies and stitches them together to create a long seamless motion in real time. Since our algorithm mainly targets on the massive quadruped animal motions, the motion graph create wide variety of different size of characters for each trajectory and automatically adjusted synthesized motions without causing artifact such as foot skating. The performance of algorithm is verified through several experiments

Introducing semantic information into motion graph

To improve motion graph based motion synthesis, semantic control was introduced. Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic aspects contained in the character’s poses of the given motion sequences. Motion templates were then automatically derived from the training motions for capturing the spatio-temporal characteristics of an entire given class of semantically related motions. The data streams of motion documents were automatically annotated with semantic motion class labels by matching their respective motion class templates. Finally, the semantic control was introduced into motion graph based human motion synthesis. Experiments of motion synthesis demonstrate the effectiveness of the approach which enables users higher level of semantically intuitive control and high quality in human motion synthesis from motion capture database.

Learning with multiple representations: an example of a revision lesson in mechanics

We describe an example of learning with multiple representations in an A-level revisionlesson on mechanics. The context of the problem involved the motion of a ball thrownvertically upwards in air and studying how the associated physical quantities changedduring its flight. Different groups of students were assigned to look at the ball’s motionusing various representations: motion diagrams, vector diagrams, free-body diagrams,verbal description, equations and graphs, drawn against time as well as againstdisplacement. Overall, feedback from students about the lesson was positive. We furtherdiscuss the benefits of using computer simulation to support and extend student learning.

Combining path planners and motion graphs

AbstractNatural locomotion of virtual characters is very important in games and simulations. The naturalness of the total motion strongly depends on both the path the character chooses and the animation of the walking character. Therefore, much work has been done on path planning and generating walking animations. However, the combination of both fields has received less attention. Combining path planning and motion synthesis introduces several problems. In this paper, we will identify two problems and propose possible solutions. The first problem is selecting an appropriate distance metric for locomotion synthesis. When concatenating clips of locomotion, a distance metric is required to detect good transition points. We have evaluated three common distance metrics both quantitatively (in terms of footskating, path deviation and online running time) and qualitatively (user study). Based on our observations, we propose a set of guidelines when using these metrics in a motion synthesizer. The second problem is the fact that there is no single point on the body that can follow the path generated by the path planner without causing unnatural animations. This raises the question how the character should follow the path. We will show that enforcing the pelvis to follow the path will lead to unnatural animations and that our proposed solution, which uses path abstractions, generates significantly better animations. Copyright © 2011 John Wiley & Sons, Ltd.

3차원 체인코드와 은닉마르코프 모델을 이용한 권투모션 인식

In this paper, a new method to recognize various motions of fighting with an aid of HMM is proposed. There are four kinds of fighting motion such as hook, jab, uppercut, and straight as the fighting motion. The motion graph is generalized to define each motion in motion data and the new 3D-chain code is used to convert motion data to motion graphs. The recognition experiment has been performed with HMM algorithm on motion graphs. The motion data is captured by a motion capture system developed in this study and by five actors. Experimental results are given with relatively high recognition rate of at least 85%.

Character animation in two-player adversarial games

The incorporation of randomness is critical for the believability and effectiveness of controllers for characters in competitive games. We present a fully automatic method for generating intelligent real-time controllers for characters in such a game. Our approach uses game theory to deal with the ramifications of the characters acting simultaneously, and generates controllers which employ both long-term planning and an intelligent use of randomness. Our results exhibit nuanced strategies based on unpredictability, such as feints and misdirection moves, which take into account and exploit the possible strategies of an adversary. The controllers are generated by examining the interaction between the rules of the game and the motions generated from a parametric motion graph. This involves solving a large-scale planning problem, so we also describe a new technique for scaling this process to higher dimensions.