1,384 research outputs found
Sketch-based skeleton-driven 2D animation and motion capture.
This research is concerned with the development of a set of novel sketch-based skeleton-driven 2D animation techniques, which allow the user to produce realistic 2D character animation efficiently. The technique consists of three parts: sketch-based skeleton-driven 2D animation production, 2D motion capture and a cartoon animation filter. For 2D animation production, the traditional way is drawing the key-frames by experienced animators manually. It is a laborious and time-consuming process. With the proposed techniques, the user only inputs one image ofa character and sketches a skeleton for each subsequent key-frame. The system then deforms the character according to the sketches and produces animation automatically. To perform 2D shape deformation, a variable-length needle model is developed, which divides the deformation into two stages: skeleton driven deformation and nonlinear deformation in joint areas. This approach preserves the local geometric features and global area during animation. Compared with existing 2D shape deformation algorithms, it reduces the computation complexity while still yielding plausible deformation results. To capture the motion of a character from exiting 2D image sequences, a 2D motion capture technique is presented. Since this technique is skeleton-driven, the motion of a 2D character is captured by tracking the joint positions. Using both geometric and visual features, this problem can be solved by ptimization, which prevents self-occlusion and feature disappearance. After tracking, the motion data are retargeted to a new character using the deformation algorithm proposed in the first part. This facilitates the reuse of the characteristics of motion contained in existing moving images, making the process of cartoon generation easy for artists and novices alike. Subsequent to the 2D animation production and motion capture,"Cartoon Animation Filter" is implemented and applied. Following the animation principles, this filter processes two types of
cartoon input: a single frame of a cartoon character and motion capture data from an image sequence. It adds anticipation and follow-through to the motion with related squash and stretch effect
Posing 3D Models from Drawing
Inferring the 3D pose of a character from a drawing is a complex and under-constrained problem. Solving it may help automate various parts of an animation production pipeline such as pre-visualisation. In this paper, a novel way of inferring the 3D pose from a monocular 2D sketch is proposed. The proposed method does not make any external assumptions about the model, allowing it to be used on different types of characters. The inference of the 3D pose is formulated as an optimisation problem and a parallel variation of the Particle Swarm Optimisation algorithm called PARAC-LOAPSO is utilised for searching the minimum. Testing in isolation as well as part of a larger scene, the presented method is evaluated by posing a lamp, a horse and a human character. The results show that this method is robust, highly scalable and is able to be extended to various types of models
Sketching-out virtual humans: A smart interface for human modelling and animation
In this paper, we present a fast and intuitive interface for sketching out
3D virtual humans and animation. The user draws stick figure key frames first and
chooses one for “fleshing-out” with freehand body contours. The system
automatically constructs a plausible 3D skin surface from the rendered figure, and
maps it onto the posed stick figures to produce the 3D character animation. A
“creative model-based method” is developed, which performs a human perception
process to generate 3D human bodies of various body sizes, shapes and fat
distributions. In this approach, an anatomical 3D generic model has been created with
three distinct layers: skeleton, fat tissue, and skin. It can be transformed sequentially
through rigid morphing, fatness morphing, and surface fitting to match the original
2D sketch. An auto-beautification function is also offered to regularise the 3D
asymmetrical bodies from users’ imperfect figure sketches. Our current system
delivers character animation in various forms, including articulated figure animation,
3D mesh model animation, 2D contour figure animation, and even 2D NPR animation
with personalised drawing styles. The system has been formally tested by various
users on Tablet PC. After minimal training, even a beginner can create vivid virtual
humans and animate them within minutes
Data-driven synthesis of realistic human motion using motion graphs
Ankara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2014.Thesis (Master's) -- Bilkent University, 2014.Includes bibliographical references leaves 53-56.Realistic human motions is an essential part of diverse range of media, such as
feature films, video games and virtual environments. Motion capture provides
realistic human motion data using sensor technology. However, motion capture
data is not flexible. This drawback limits the utility of motion capture in practice.
In this thesis, we propose a two-stage approach that makes the motion captured
data reusable to synthesize new motions in real-time via motion graphs. Starting
from a dataset of various motions, we construct a motion graph of similar motion
segments and calculate the parameters, such as blending parameters, needed in
the second stage. In the second stage, we synthesize a new human motion in realtime,
depending on the blending techniques selected. Three different blending
techniques, namely linear blending, cubic blending and anticipation-based blending,
are provided to the user. In addition, motion clip preference approach, which
is applied to the motion search algorithm, enable users to control the motion clip
types in the result motion.Dirican, HüseyinM.S
DualMotion: Global-to-Local Casual Motion Design for Character Animations
Animating 3D characters using motion capture data requires basic expertise
and manual labor. To support the creativity of animation design and make it
easier for common users, we present a sketch-based interface DualMotion, with
rough sketches as input for designing daily-life animations of characters, such
as walking and jumping.Our approach enables to combine global motions of lower
limbs and the local motion of the upper limbs in a database by utilizing a
two-stage design strategy. Users are allowed to design a motion by starting
with drawing a rough trajectory of a body/lower limb movement in the global
design stage. The upper limb motions are then designed by drawing several more
relative motion trajectories in the local design stage. We conduct a user study
and verify the effectiveness and convenience of the proposed system in creative
activities.Comment: 10 pages, 10 figures, under submission, video is here
https://youtu.be/-tk8q8LSiL
Real Time Animation of Virtual Humans: A Trade-off Between Naturalness and Control
Virtual humans are employed in many interactive applications using 3D virtual environments, including (serious) games. The motion of such virtual humans should look realistic (or ‘natural’) and allow interaction with the surroundings and other (virtual) humans. Current animation techniques differ in the trade-off they offer between motion naturalness and the control that can be exerted over the motion. We show mechanisms to parametrize, combine (on different body parts) and concatenate motions generated by different animation techniques. We discuss several aspects of motion naturalness and show how it can be evaluated. We conclude by showing the promise of combinations of different animation paradigms to enhance both naturalness and control
Sketch-based Human Motion Retrieval via 2D Geometric Posture Descriptor.
AbstractSketch-based human motion retrieval is a hot topic in computer animation in recent years. In this paper, we present a novel sketch-based human motion retrieval method via selected 2-dimensional (2D) Geometric Posture Descriptor (2GPD). Specially, we firstly propose a rich 2D pose feature call 2D Geometric Posture Descriptor (2GPD), which is effective in encoding the 2D posture similarity by exploiting the geometric relationships among different human body parts. Since the original 2GPD is of high dimension and redundant, a semi-supervised feature selection algorithm derived from Laplacian Score is then adopted to select the most discriminative feature component of 2GPD as feature representation, and we call it as selected 2GPD. Finally, a posture-by-posture motion retrieval algorithm is used to retrieve a motion sequence by sketching several key postures. Experimental results on CMU human motion database demonstrate the effectiveness of our proposed approach
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Generating 3D product design models in real-time using hand motion and gesture
This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University.Three dimensional product design models are widely used in conceptual design and in the early stage of prototyping during the design processes. A product design specification often demands a substantial amount of 3D models to be constructed within a short period of time. Current methods begin with designers sketching product concepts in 2D using pencil and paper, which in turn are then translated into 3D models by a design individual with CAD expertise, using a 3D modelling software package such as Pro Engineer, Solid Works, Auto CAD etc. Several novel methods have been used to incorporate hand motion as a way of interacting with computers. There are three main types of technology available to capture motion data, capable of translating human motion into numeric data which can be read by a computer system. The first being, hand gesture glove-based systems such as “Cyberglove”, these systems are generally used to capture hand gesture and joint angle information. The second is full body motion capture systems, optical and non-optical-based, and finally vision based gesture recognition systems which capture full degree of - freedom (DOF) hand motion estimation. There has yet to be a method using any of the above mentioned input devices to rapidly produce 3D product design models in real time, using hand motion and gestures. In this research, a novel method is presented, using a motion capture system to capture hand gestures and motion in real time, to recreate 3D curves and surfaces, which can be translated into 3D product design models. The main aim of this research is to develop a hand motion and gesture-based rapid 3D product modelling method, allowing designers to interactively sketch out 3D concepts in real time using a virtual workspace.
A database of a number of hand signs was built for both architectural hand signs (preliminary study) and Product Design hand signs. A marker set model with a total of eight markers (five on the left hand and three on right hand/marker pen) was designed and used in the capture of hand gestures with the use of an Optical Motion Capture System. A preliminary testing session was successfully completed to determine whether the Motion Capture system would be suitable for a real-time application, by effectively modelling a train station in an offline state using hand motion and gesture. An OpenGL software application was programmed using C++ and the Microsoft Foundation Classes which was used to communicate and pass information of captured motion from the EVaRT system to the user
Space-time sketching of character animation
International audienceWe present a space-time abstraction for the sketch-based design of character animation. It allows animators to draft a full coordinated motion using a single stroke called the space-time curve (STC). From the STC we compute a dynamic line of action (DLOA) that drives the motion of a 3D character through projective constraints. Our dynamic models for the line's motion are entirely geometric, require no pre-existing data, and allow full artistic control. The resulting DLOA can be refined by over-sketching strokes along the space-time curve, or by composing another DLOA on top leading to control over complex motions with few strokes. Additionally , the resulting dynamic line of action can be applied to arbitrary body parts or characters. To match a 3D character to the 2D line over time, we introduce a robust matching algorithm based on closed-form solutions, yielding a tight match while allowing squash and stretch of the character's skeleton. Our experiments show that space-time sketching has the potential of bringing animation design within the reach of beginners while saving time for skilled artists
Modeling and generating moving trees from video
We present a probabilistic approach for the automatic production of tree models with convincing 3D appearance and motion. The only input is a video of a moving tree that provides us an initial dynamic tree model, which is used to generate new individual trees of the same type. Our approach combines global and local constraints to construct a dynamic 3D tree model from a 2D skeleton. Our modeling takes into account factors such as the shape of branches, the overall shape of the tree, and physically plausible motion. Furthermore, we provide a generative model that creates multiple trees in 3D, given a single example model. This means that users no longer have to make each tree individually, or specify rules to make new trees. Results with different species are presented and compared to both reference input data and state of the art alternatives
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