https://www.ee.columbia.edu/%7Eajaimes/Pubs/ajaimes_iccv05.pdf

Multimodal human-computer interaction: A survey

In this paper we review the major approaches to multimodal human computer interaction from a computer vision perspective. In particular, we focus on body, gesture, gaze, and affective interaction (facial expression recognition, and emotion in audio). We discuss user and task modeling, and multimodal fusion, highlighting challenges, open issues, and emerging applications for Multimodal Human Computer Interaction (MMHCI) research.

Multimodal human computer interaction: a survey

The intention of this paper is to provide an overview on the subject of Human-Computer Interaction. The overview includes the basic definitions and terminology, a survey of existing technologies and recent advances in the field, common architectures used in the design of HCI systems which includes unimodal and multimodal configurations, and finally the applications of HCI. This paper also offers a comprehensive number of references for each concept, method, and application in the HCI.

Human-Computer Interaction: Overview on State of the Art

Emotions are an integral component of all human activities, including human-computer interactions. This article reviews literature on the theories of emotions, methods for studying emotions, and their role in human information behaviour. It also examines current research on emotions in library and information science, information retrieval and human-computer interaction, and outlines some of the challenges and directions for future work.

Theories, methods and current research on emotions in library and information science, information retrieval and human-computer interaction

Vision-based human action recognition provides an advanced interface, and research in the field of human action recognition has been actively carried out. However, an environment from dynamic viewpoint, where we can be in any position, any direction, etc., must be considered in our living 3D space. In order to overcome the viewpoint dependency, we propose a Volume Motion Template (VMT) and Projected Motion Template (PMT). The proposed VMT method is an extension of the Motion History Image (MHI) method to 3D space. The PMT is generated by projecting the VMT into a 2D plane that is orthogonal to an optimal virtual viewpoint where the optimal virtual viewpoint is a viewpoint from which an action can be described in greatest detail, in 2D space. From the proposed method, any actions taken from different viewpoints can be recognized independent of the viewpoints. The experimental results demonstrate the accuracies and effectiveness of the proposed VMT method for view-independent human action recognition.

View-independent human action recognition with Volume Motion Template on single stereo camera

For the real-time recognition of unspecified gestures by an arbitrary person, a comprehensive framework is presented that addresses two important problems in gesture recognition systems: selective attention and processing frame rate. To address the first problem, we propose the Quadruple Visual Interest Point Strategy. No assumptions are made with regard to scale or rotation of visual features, which are computed from dynamically changing regions of interest in a given image sequence. In this paper, each of the visual features is referred to as a visual interest point, to which a probability density function is assigned, and the selection is carried out. To address the second problem, we developed a selective control method to equip the recognition system with self-load monitoring and controlling functionality. Through evaluation experiments, we show that our approach provides robust recognition with respect to such factors as type of clothing, type of gesture, extent of motion trajectories, and individual differences in motion characteristics. In order to indicate the real-time performance and utility aspects of our approach, a gesture video system is developed that demonstrates full video-rate interaction with displayed image objects.

Real-time gesture recognition by learning and selective control of visual interest points

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

K. Chihara

Author Tools

Chat about Author

Papers

Real-time gesture recognition by learning and selective control of visual interest points