Vection induced by low-level motion extracted from complex animation films

This study examined the contributions of low-, mid- and high-level visual motion information to vection. We compared the vection experiences induced by hand-drawn and computer-generated animation clips to those induced by versions of these movies that contained only their pure optic flow. While the original movies were found to induce longer and stronger vection experiences than the pure optic flow, vection onsets were not significantly altered by removing the mid- and high-level information. We conclude that low-level visual motion information appears to be important for vection induction, whereas mid- and higher-level display information appears to be important for sustaining and strengthening this vection after its initial induction

Augmenting the Creation of 3D Character Motion By Learning from Video Data

When it comes to character motions, especially articulated character animation, the majority of efforts are spent on accurately capturing the low level and high level action styles. Among the many techniques which have evolved over the years, motion capture (mocap) and key frame animations are the two popular choices. Both techniques are capable of capturing the low level and high level action styles of a particular individual, but at great expense in terms of the human effort involved. In this thesis, we make use of performance data in video format to augment the process of character animation, considerably decreasing human effort for both style preservation and motion regeneration. Two new methods, one for high-level and another for low-level character animation, which are based on learning from video data to augment the motion creation process, constitute the major contribution of this research. In the first, we take advantage of the recent advancements in the field of action recognition to automatically recognize human actions from video data. High level action patterns are learned and captured using Hidden Markov Models (HMM) to generate action sequences with the same pattern. For the low level action style, we present a completely different approach that utilizes user-identified transition frames in a video to enhance the transition construction in the standard motion graph technique for creating smooth action sequences. Both methods have been implemented and a number of results illustrating the concept and applicability of the proposed approach are presented

A motion system for social and animated robots

This paper presents an innovative motion system that is used to control the motions and animations of a social robot. The social robot Probo is used to study Human-Robot Interactions (HRI), with a special focus on Robot Assisted Therapy (RAT). When used for therapy it is important that a social robot is able to create an "illusion of life" so as to become a believable character that can communicate with humans. The design of the motion system in this paper is based on insights from the animation industry. It combines operator-controlled animations with low-level autonomous reactions such as attention and emotional state. The motion system has a Combination Engine, which combines motion commands that are triggered by a human operator with motions that originate from different units of the cognitive control architecture of the robot. This results in an interactive robot that seems alive and has a certain degree of "likeability". The Godspeed Questionnaire Series is used to evaluate the animacy and likeability of the robot in China, Romania and Belgium

A survey of comics research in computer science

Graphical novels such as comics and mangas are well known all over the world. The digital transition started to change the way people are reading comics, more and more on smartphones and tablets and less and less on paper. In the recent years, a wide variety of research about comics has been proposed and might change the way comics are created, distributed and read in future years. Early work focuses on low level document image analysis: indeed comic books are complex, they contains text, drawings, balloon, panels, onomatopoeia, etc. Different fields of computer science covered research about user interaction and content generation such as multimedia, artificial intelligence, human-computer interaction, etc. with different sets of values. We propose in this paper to review the previous research about comics in computer science, to state what have been done and to give some insights about the main outlooks

Movies and meaning: from low-level features to mind reading

When dealing with movies, closing the tremendous discontinuity between low-level features and the richness of semantics in the viewers' cognitive processes, requires a variety of approaches and different perspectives. For instance when attempting to relate movie content to users' affective responses, previous work suggests that a direct mapping of audio-visual properties into elicited emotions is difficult, due to the high variability of individual reactions. To reduce the gap between the objective level of features and the subjective sphere of emotions, we exploit the intermediate representation of the connotative properties of movies: the set of shooting and editing conventions that help in transmitting meaning to the audience. One of these stylistic feature, the shot scale, i.e. the distance of the camera from the subject, effectively regulates theory of mind, indicating that increasing spatial proximity to the character triggers higher occurrence of mental state references in viewers' story descriptions. Movies are also becoming an important stimuli employed in neural decoding, an ambitious line of research within contemporary neuroscience aiming at "mindreading". In this field we address the challenge of producing decoding models for the reconstruction of perceptual contents by combining fMRI data and deep features in a hybrid model able to predict specific video object classes

Real Time Virtual Humans

The last few years have seen great maturation in the computation speed and control methods needed to portray 3D virtual humans suitable for real interactive applications. Various dimensions of real-time virtual humans are considered, such as appearance and movement, autonomous action, and skills such as gesture, attention, and locomotion. A virtual human architecture includes low level motor skills, mid-level PaT-Net parallel finite-state machine controller, and a high level conceptual action representation that can be used to drive virtual humans through complex tasks. This structure offers a deep connection between natural language instructions and animation control