Computer Animation and Virtual Worlds

Top Research Topics at Computer Animation and Virtual Worlds?

The journal was organized to reinforce research efforts on Artificial intelligence, Computer vision, Computer graphics (images), Animation and Human–computer interaction. Artificial intelligence research presented in Computer Animation and Virtual Worlds encompasses a variety of subjects, including Character animation, Computer facial animation and Character (mathematics). Computer Animation and Virtual Worlds focused on Computer facial animation research but expanded to cover Facial expression.

The Computer vision research presented places emphasis on topics like Face (geometry), Image (mathematics) and Feature (computer vision). In it, Object (computer science) and Surface (mathematics) are investigated in conjunction with one another to address concerns in Computer graphics (images) research. It links adjacent topics like Animation with Simulation.

The research on Human–computer interaction discussed in it draws on the closely related field of Multimedia. Discussions in it are anchored in the subject of Polygon mesh and the similar topic of Algorithm.

• Artificial intelligence (39.32%)
• Computer vision (27.85%)
• Computer graphics (images) (24.56%)

What are the most cited papers published in the journal?

• Capturing human motion using body-fixed sensors: Outdoor measurement and clinical applications (214 citations)
• Synthesizing multimodal utterances for conversational agents (213 citations)
• A survey of mobile and wireless technologies for augmented reality systems (191 citations)

Research areas of the most cited articles at Computer Animation and Virtual Worlds:

The most cited articles mainly tackle studies in Artificial intelligence, Computer vision, Computer graphics (images), Simulation and Animation. Issues in Artificial intelligence were discussed in the journal papers, taking into consideration concepts from other disciplines like Computer facial animation and Speech recognition. In addition to Computer vision research, the published papers aim to explore topics under Motion planning, Avatar and Character (mathematics).

What topics the last edition of the journal is best known for?

• Artificial intelligence
• Computer vision
• Programming language

The previous edition focused in particular on these issues:

The aim of Computer Animation and Virtual Worlds is to expand the discussion of research in Artificial intelligence, Computer vision, Human–computer interaction, Virtual reality and Engineering ethics. The in-depth study on Artificial intelligence also explores topics in the intersecting field of Boundary (topology). Some problems in Computer vision that were presented in it overlapped with concepts under Movement (music) and Collision detection.

The studies in Human–computer interaction featured incorporate elements of Animation, Crowd simulation, Aircraft maintenance and Gesture recognition. It holds forums on Animation that merges themes from other disciplines such as Artificial neural network, Object (computer science), Interactive design, Key (cryptography) and Reinforcement learning. In addition to Virtual reality research, the journal aims to explore topics under Virtual machine, Affect (psychology) and Embodied cognition.

The most cited articles from the last journal are:

• Synthesizing Large‐Scale Fluid Simulations with Surface and Wave Foams via Sharp Wave Pattern and Cloudy Foam (3 citations)
• PhyCoVIS: A visual analytic tool of physical coordination for cheer and dance training (2 citations)
• A simplified force model for mixed traffic simulation (2 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing in Computer Animation and Virtual Worlds (based on the number of publications) are:

• Daniel Thalmann (37 papers) published 1 paper at the last edition, 3 less than at the previous edition,
• Nadia Magnenat-Thalmann (33 papers) absent at the last edition,
• Xiaogang Jin (29 papers) published 2 papers at the last edition the same number as at the previous edition,
• Enhua Wu (24 papers) published 2 papers at the last edition, 2 less than at the previous edition,
• Xiaosong Yang (22 papers) published 1 paper at the last edition, 2 less than at the previous edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Computer Animation and Virtual Worlds (based on the number of publications) are:

• Zhejiang University (96 papers) published 6 papers at the last edition, 3 more than at the previous edition,
• Bournemouth University (42 papers) published 4 papers at the last edition, 2 less than at the previous edition,
• Chinese Academy of Sciences (40 papers) published 3 papers at the last edition, 1 less than at the previous edition,
• Nanyang Technological University (30 papers) published 1 paper at the last edition,
• KAIST (29 papers) published 1 paper at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 3.77% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 37.25% were posted by at least one author from the top 10 institutions publishing in the journal. Another 5.88% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 29.41% of all publications and 27.45% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Educational Requirements for Researchers

In order to contribute significantly to research efforts, especially in highly specialized fields such as Artificial Intelligence, Computer Vision, and Virtual Worlds, it's crucial that researchers acquire relevant expertise through comprehensive and cutting-edge educational programs.

Several universities offer specialized degrees and certificate programs that cater to these rapidly advancing fields. For instance, computer science programs may include coursework in AI and Computer Vision, while animation programs cover topics such as character animation and facial animation, relevant to virtual worlds.

In a related vein, individuals interested in applying technology to education fields, such as special education, can acquire qualifications like a [special education certification online ohio]. Such certifications help link the advanced technological capabilities with specialized teaching techniques, contributing to the transformative effect that these technologies can have in specialized educational environments.

As the fields of Computer Animation and Virtual Worlds continue to grow and evolve, so does the need for researchers and practitioners who are well equipped with the necessary knowledge and skills. Therefore, seeking the appropriate education and training is a crucial step for those who wish to contribute to these exciting areas of study and application.