10,526 research outputs found
Fast Preprocessing for Robust Face Sketch Synthesis
Exemplar-based face sketch synthesis methods usually meet the challenging
problem that input photos are captured in different lighting conditions from
training photos. The critical step causing the failure is the search of similar
patch candidates for an input photo patch. Conventional illumination invariant
patch distances are adopted rather than directly relying on pixel intensity
difference, but they will fail when local contrast within a patch changes. In
this paper, we propose a fast preprocessing method named Bidirectional
Luminance Remapping (BLR), which interactively adjust the lighting of training
and input photos. Our method can be directly integrated into state-of-the-art
exemplar-based methods to improve their robustness with ignorable computational
cost.Comment: IJCAI 2017. Project page:
http://www.cs.cityu.edu.hk/~yibisong/ijcai17_sketch/index.htm
Sketching-out virtual humans: From 2d storyboarding to immediate 3d character animation
Virtual beings are playing a remarkable role in todayâs public entertainment, while ordinary users are still treated as audiences due to the lack of appropriate expertise, equipment, and computer skills. In this paper, we present a fast and intuitive storyboarding interface, which enables users to sketch-out 3D virtual humans, 2D/3D animations, and character intercommunication. We devised an intuitive âstick figurefleshing-outskin mappingâ graphical animation pipeline, which realises the whole process of key framing, 3D pose reconstruction, virtual human modelling, motion path/timing control, and the final animation synthesis by almost pure 2D sketching. A âcreative model-based methodâ is developed, which emulates a human perception process, to generate the 3D human bodies of variational sizes, shapes, and fat distributions. Meanwhile, our current system also supports the sketch-based crowd animation and the storyboarding of the 3D multiple character intercommunication. This 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
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Shape interpretation with design computing
How information is interpreted has significant impact on how it can be used. This is particularly important in design where information from a wide variety of sources is used in a wide variety of contexts and in a wide variety of ways. This paper is concerned with the information that is created, modified and analysed during design processes, specifically with the information that is represented in shapes. It investigates how design computing seeks to support these processes, and the difficulties that arise when it is necessary to consider alternative interpretations of shape. The aim is to establish the problem of shape interpretation as a general challenge for research in design computing, rather than a difficulty that is to be overcome within specific processes. Shape interpretations are common characteristics of several areas of enquiry in design computing. This paper reviews these, brings an integrated perspective and draws conclusions about how this underlying process can be supported
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 âfleshing-outâ 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
âcreative model-based methodâ 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 usersâ 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
Deep Sketch-Photo Face Recognition Assisted by Facial Attributes
In this paper, we present a deep coupled framework to address the problem of
matching sketch image against a gallery of mugshots. Face sketches have the
essential in- formation about the spatial topology and geometric details of
faces while missing some important facial attributes such as ethnicity, hair,
eye, and skin color. We propose a cou- pled deep neural network architecture
which utilizes facial attributes in order to improve the sketch-photo
recognition performance. The proposed Attribute-Assisted Deep Con- volutional
Neural Network (AADCNN) method exploits the facial attributes and leverages the
loss functions from the facial attributes identification and face verification
tasks in order to learn rich discriminative features in a common em- bedding
subspace. The facial attribute identification task increases the inter-personal
variations by pushing apart the embedded features extracted from individuals
with differ- ent facial attributes, while the verification task reduces the
intra-personal variations by pulling together all the fea- tures that are
related to one person. The learned discrim- inative features can be well
generalized to new identities not seen in the training data. The proposed
architecture is able to make full use of the sketch and complementary fa- cial
attribute information to train a deep model compared to the conventional
sketch-photo recognition methods. Exten- sive experiments are performed on
composite (E-PRIP) and semi-forensic (IIIT-D semi-forensic) datasets. The
results show the superiority of our method compared to the state- of-the-art
models in sketch-photo recognition algorithm
Paper-based Mixed Reality Sketch Augmentation as a Conceptual Design Support Tool
This undergraduate student paper explores usage of mixed reality techniques as support tools for conceptual design. A proof-of-concept was developed to illustrate this principle. Using this as an example, a small group of designers was interviewed to determine their views on the use of this technology. These interviews are the main contribution of this paper. Several interesting applications were determined, suggesting possible usage in a wide range of domains. Paper-based sketching, mixed reality and sketch augmentation techniques complement each other, and the combination results in a highly intuitive interface
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