Automating the creation of 3D animation from annotated fiction text

This paper describes a strategy for automatically converting fiction text into 3D animations. It assumes the existence of fiction text annotated with avatar, object, setting, transition and relation annotations, and presents a transformation process that converts annotated text into quantified constraint systems, the solutions to which are used in the population of 3D environments. Constraint solutions are valid over temporal intervals, ensuring that consistent dynamic behaviour is produced. A substantial level of automation is achieved, while providing opportunities for creative manual intervention in animation process. The process is demonstrated using annotated examples drawn from popular fiction text that are converted into animation sequences, confirming that the desired results can be achieved with only high-level human direction.

A method for automatically creating 3D animated scenes from annotated fiction text

This paper describes a strategy for automatically converting fiction text into 3D animations. It assumes the existence of fiction text annotated with avatar, object, setting, transition and relation annotations, and presents a transformation process that converts annotated text into quantified constraint systems, the solutions to which are used in the population of 3D environments. Constraint solutions are valid over temporal intervals, ensuring that consistent dynamic behaviour is produced. A substantial level of automation is achieved, while providing opportunities for creative manual intervention in animation process. The process is demonstrated using annotated examples drawn from popular fiction text that are converted into animation sequences, confirming that the desired results can be achieved with only highlevel human direction.

Human action recognition based on 3D SIFT and LDA model

How to recognize human action from videos captured by modern cameras efficiently and effectively is a challenge in real applications. Traditional methods which need professional analysts are facing a bottleneck because of their shortcomings. To cope with the disadvantage, methods based on computer vision techniques, without or with only a few human interventions, have been proposed to analyse human actions in videos automatically. This paper provides a method combining the three dimensional Scale Invariant Feature Transform (SIFT) detector and the Latent Dirichlet Allocation (LDA) model for human motion analysis. To represent videos effectively and robustly, we extract the 3D SIFT descriptor around each interest point, which is sampled densely from 3D Space-time video volumes. After obtaining the representation of each video frame, the LDA model is adopted to discover the underlying structure-the categorization of human actions in the collection of videos. Public available standard datasets are used to test our method. The concluding part discusses the research challenges and future directions.

Stereo vision and wavelets/multiwavelets analysis : 3d reconstruction using wavelets/multiwavelets theory and stereo vision

During the image formation process of the camera, explicit 3D information about the scene or objects in the scene are lost. Therefore, 3D structure or depth information has to be inferred implicitly from the 2D intensity images. This problem is com- monly referred to as 3D reconstruction. In this work a complete 3D reconstruction algorithm is presented, capable of reconstructing dimensionally accurate 3D models of the objects, based on stereo vision and multi-resolution analysis. The developed system uses a reference depth model of the objects under observation to improve the disparity maps, estimated. Only a few features are extracted from that reference model, which are the relative location of the discontinuities and the z-dimensional extremes of objects depth. The maximum error deviation of the estimated depth along the surfaces is less than 0.5mm and along the discontinuities is less than 1.5mm. The developed system is invariant to illuminative variations, and orientation, location and scaling of the objects under consideration, which makes the developed system highly robust.

Emerging hypothesis verification using function-based geometric models and active vision strategies

This paper describes an investigation into the use of parametric 2D models describing the movement of edges for the determination of possible 3D shape and hence function of an object. An assumption of this research is that the camera can foveate and track particular features. It is argued that simple 2D analytic descriptions of the movement of edges can infer 3D shape while the camera is moved. This uses an advantage of foveation i.e. the problem becomes object centred. The problem of correspondence for numerous edge points is overcome by the use of a tree based representation for the competing hypotheses. Numerous hypothesis are maintained simultaneously and it does not rely on a single kinematic model which assumes constant velocity or acceleration. The numerous advantages of this strategy are described.

Predatory vision : 3D imaging and the transformation of screen-space

Despite Wheatstone’s academic interests in the device, the stereoscope languished somewhat as an optical toy. Yet the advent of 3D screen-spaces for home and mass entertainment suggests today’s consumers and practitioners of screen culture hold the view that screen culture will be ‘improved’ through 3D imaging technologies. Like cinema and photography, stereoscopic 3D imaging has the potential to transform visual culture. But what is transformed, as optics and electronic imaging techniques deliver Alice in Wonderland in 3D? This paper links the advent of 3D cinema and TV to the notion that vision is itself a ‘technology of the visual’. As such, our innate binocular stereoacuity is ripe for exploitation by developers of 3D imaging technologies. I argue that contemporary 3D imaging marks an epistemological visual-perceptual shift: toward screenspaces becoming spaces for potential action. Such a shift entails seeing as doing rather than seeing as thinking. 3D imaging exploits binocular vision’s spatial acuity (stereopsis), but is effective only for objects within near distal space. The 3D effect tapers off dramatically for objects only some metres away, because the two retinal images lack significant lateral disparity (difference) to trigger stereopsis: the imagery flattens out and becomes ‘monoscopic’. Information available from conventional 2D media entails a peculiarly unspecified spatiality. Perceptually, the contents of a conventional cinematic screen are like those of a painting: they are situated neither near nor far, and constitute a shared and ambiguous visual space. Our own eyes are like those of a cat: frontally placed for predatory action. The visuality of 3D screen-spaces assumes a perceptuality of the near-by and close at hand, since this is the structure of the visible information to which stereopsis is adapted to respond. Noting the binocular acuity of predatory animals, as well as some etymological links, this paper examines the implications of perceptually ‘capturing’ the sensation of visually solid objects in one’s immediate space. Stereopsis is about decisive action within an immediate environment: but it also presupposes the single viewpoint of an active observer toward which the 3D imagery is targeted.

Localisation of an object in motion in 3D space via angle only measurements

In this paper, we discuss an approach to localisation of a moving object in 3D space. The method used to track this object is angle only measurements obtained via radar elements strategically placed within the X, Y and Z planes. In addition, computer simulations are conducted to verify the theoretical assertions presented with respect to the application employing an Extended Kalman Filter.

Collaboration in 3D shared spaces using X3D and VRML

We propose a framework for visual and haptic collaboration in 3D shared virtual spaces. Virtual objects can de declared as shared objects which visual and physical properties are rendered synchronously on each client computer. We introduce virtual tools which are shared objects associated with interactive and haptic devices. We implement the proposed ideas as new pilot versions of BS Collaborate server and BS Contact VRML/X3D viewer. In our collaborative framework, two pipelines-visual and haptic-complement each other to provide a simple and efficient solution to problem requiring collaboration in shared virtual spaces on the Web. We discuss two implementation frameworks based on the strong and thin server concepts.

Extracting 3D mesh skeletons using antipodal points locations

Finding the skeleton of a 3D mesh is an essential task for many applications such as mesh animation, tracking, and 3D registeration. In recent years, new technologies in computer vision such as Microsoft Kinect have proven that a mesh skeleton can be useful such as in the case of human machine interactions. To calculate the 3D mesh skeleton, the mesh properties such as topology and its components relations are utilized. In this paper, we propose the usage of a novel algorithm that can efficiently calculate a vertex antipodal point. A vertex antipodal point is the diametrically opposite point that belongs to the same mesh. The set of centers of the connecting lines between each vertex and its antipodal point represents the 3D mesh desired skeleton. Post processing is completed for smoothing and fitting centers into optimized skeleton parts. The algorithm is tested on different classes of 3D objects and produced efficient results that are comparable with the literature. The algorithm has the advantages of producing high quality skeletons as it preserves details. This is suitable for applications where the mesh skeleton mapping is required to be kept as much as possible.

Towards a parameterless 3D mesh segmentation

This paper proposes a novel technique for 3D mesh segmentation using multiple 2D pose footprints. Such problem has been targeted many times in the literature, but still requires further development especially in the area of automation. The proposed algorithm applies cognition theory and provides a generic technique to form a 3D bounding contour from a seed vertex on the 3D mesh. Forming the cutlines is done in both 2D and 3D spaces to enrich the available information for the search processes. The main advantage of this technique is the possibility to operate without any object-dependent parameters. The parameters that can be used will only be related to the used cognition theory and the seeds suggestion, which is another advantage as the algorithm can be generic to more than one theory of segmentation or to different criterion. The results are competitive against other algorithms, which use object-dependent or tuning parameters. This plus the autonomy and generality features, provides an efficient and usable approach for segmenting 3D meshes and at the same time to reduce the computation load.

Lab-on-a-Chip turns soft : computer-aided, software-enabled microfluidics design

The current practice of designing microfluidic Lab-on-a-Chip (LoCs) limits reusing designs and makes sharing tasks among researchers difficult. One way to achieve that objective is to borrow best practices from engineering. Also it takes a lot of skills to design LoCs. Design-by-assembly in which a LoC can be designed by configuring, laying out subsystems can help new researchers to develop custom chips. Flexible, reusable, and rapid-prototyping-feasible LoC designs can be achieved by fabricated modular microfluidic blocks. However, challenging problems still persist, which limit the usefulness of prefabricated blocks. We propose software microfluidic modules (SoftMABs) based design technique to solve issues fabricated modules face. By configuring SoftMABs, integrating them, the new assembly of SoftMABs can form a 3D LoC design ready to be prototyped. The proposed method can make designing a complex LoC less challenging, and collaborating among laboratories easier. We created SoftMABs and designed a custom microfluidic chip by assembling SoftMABs like LEGOs, dragging-and-dropping them. Later we reconfigured them - by replacing a SoftMAB with another module - to make a new LoC. We believe this computeraided method is an interesting and useful LoC design technique.

Efficacy comparison of clustering systems for limb detection

This paper presents a comparison of applying different clustering algorithms on a point cloud constructed from the depth maps captured by a RGBD camera such as Microsoft Kinect. The depth sensor is capable of returning images, where each pixel represents the distance to its corresponding point not the RGB data. This is considered as the real novelty of the RGBD camera in computer vision compared to the common video-based and stereo-based products. Depth sensors captures depth data without using markers, 2D to 3D-transition or determining feature points. The captured depth map then cluster the 3D depth points into different clusters to determine the different limbs of the human-body. The 3D points clustering is achieved by different clustering techniques. Our Experiments show good performance and results in using clustering to determine different human-body limbs.