No abstract

No abstract

Virtual characters are much in demand for animated movies, games, and other applications. Rapid advances in performance capture and advanced rendering techniques have allowed the movie industry in particular to create characters that appear very human-like. However, with these new capabilities has come the realization that such characters are yet not quite "right." One possible hypothesis is that these virtual humans fall into an "Uncanny Valley", where the viewer's emotional response is repulsion or rejection, rather than the empathy or emotional engagement that their creators had hoped for. To explore these issues, we created three animated vignettes of an arguing couple with detailed motion for the face, eyes, hair, and body. In a set of perceptual experiments, we explore the relative importance of different anomalies using two different methods: a questionnaire to determine the emotional response to the full-length vignettes, with and without facial motion and audio; and a 2AFC (two alternative forced choice) task to compare the performance of a virtual "actor" in short clips (extracts from the vignettes) depicting a range of different facial and body anomalies. We found that the facial anomalies are particularly salient, even when very significant body animation anomalies are present.

Figure 1: Animations with synthesized finger motions: (a) ok gesture, (b)-(c) extracts from a conversation, (d) attention gesture. AbstractCapturing the body movements of actors to create animations for movies, games, and VR applications has become standard practice, but finger motions are usually added manually as a tedious postprocessing step. In this paper, we present a surprisingly simple method to automate this step for gesturing and conversing characters. In a controlled environment, we carefully captured and post-processed finger and body motions from multiple actors. To augment the body motions of virtual characters with plausible and detailed finger movements, our method selects finger motion segments from the resulting database taking into account the similarity of the arm motions and the smoothness of consecutive finger motions. We investigate which parts of the arm motion best discriminate gestures with leave-one-out cross-validation and use the result as a metric to select appropriate finger motions. Our approach provides good results for a number of examples with different gesture types and is validated in a perceptual experiment.

Digital games with realistic virtual characters have become very popular. The ability for players to promptly control their character is a crucial feature of these types of games, be it platform games, first-person shooters, or role-playing games. Controller latencies, meaning delays in the responsiveness of a player's character, for example due to extensive computations or to network latencies, can considerably reduce the player's enjoyment of a game. In this paper, we present a thorough analysis of the consequences of such delays on the player's experience across three parts of a game with different levels of difficulty. We investigate the effects of responsiveness on the player's enjoyment, performance, and perception of the game, as well as the player's adaptability to delays. We find that responsiveness is very important for the player as delays affect the player's enjoyment of the game as well as the player's performance. A quick responsiveness becomes essential for more challenging tasks. AbstractDigital games with realistic virtual characters have become very popular. The ability for players to promptly control their character is a crucial feature of these types of games, be it platform games, first-person shooters, or role-playing games. Controller latencies, meaning delays in the responsiveness of a player's character, for example due to extensive computations or to network latencies, can considerably reduce the player's enjoyment of a game. In this paper, we present a thorough analysis of the consequences of such delays on the player's experience across three parts of a game with different levels of difficulty. We investigate the effects of responsiveness on the player's enjoyment, performance, and perception of the game, as well as the player's adaptability to delays. We find that responsiveness is very important for the player as delays affect the player's enjoyment of the game as well as the player's performance. A quick responsiveness becomes essential for more challenging tasks.

The human hand is a complex biological system able to perform numerous tasks with impressive accuracy and dexterity. Gestures furthermore play an important role in our daily interactions, and humans are particularly skilled at perceiving and interpreting detailed signals in communications. Creating believable hand motions for virtual characters is an important and challenging task. Many new methods have been proposed in the Computer Graphics community within the last years, and significant progress has been made towards creating convincing, detailed hand and finger motions. This state of the art report presents a review of the research in the area of hand and finger modeling and animation. Starting with the biological structure of the hand and its implications for how the hand moves, we discuss current methods in motion capturing hands, data‐driven and physics‐based algorithms to synthesize their motions, and techniques to make the appearance of the hand model surface more realistic. We then focus on areas in which detailed hand motions are crucial such as manipulation and communication. Our report concludes by describing emerging trends and applications for virtual hand animation.

This paper introduces a method for producing high quality hand motion using a small number of markers. The proposed "handover" animation technique constructs joint angle trajectories with the help of a reference database. Utilizing principle component analysis (PCA) applied to the database, the system automatically determines the sparse marker set to record. Further, to produce hand animation, PCA is used along with a locally weighted regression (LWR) model to reconstruct joint angles. The resulting animation is a full-resolution hand which reflects the original motion without the need for capturing a full marker set. Comparing the technique to other methods reveals improvement over the state of the art in terms of the marker set selection. In addition, the results highlight the ability to generalize the motion synthesized, both by extending the use of a single reference database to new motions, and from distinct reference datasets, over a variety of freehand motions.

In order to analyze the emotional content of motions portrayed by different characters, we created real and virtual replicas of an actor exhibiting six basic emotions: sadness, happiness, surprise, fear, anger, and disgust. In addition to the video of the real actor, his actions were applied to five virtual body shapes: a low-and high-resolution virtual counterpart, a cartoon-like character, a wooden mannequin, and a zombie-like character (Figures 1 and 2). In a point light condition, we also tested whether the absence of a body affected the perceived emotion of the movements. Participants were asked to rate the actions based on a list of 41 more complex emotions. We found that the perception of emotional actions is highly robust and to the most part independent of the character's body, so long as form is present. When motion alone is present, emotions were generally perceived as less intense than in the cases where form was present.