Computer Vision Face Tracking For Use in a Perceptual User Interface
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Summary
The mean shift algorithm is modified to deal with dynamically changing color probability distributions derived from video frame sequences, called the Continuously Adaptive Mean Shift (CAMSHIFT), which is used as a computer interface for controlling commercial computer games and for exploring immersive 3D graphic worlds.
- Type
- article
- Published
- 1998-01-01
- Cited by
- 1,794
- References
- 25
- OpenAlex
- https://openalex.org/W1502024436
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:2928235
Keywords
Computer science, Computer vision, Artificial intelligence, Perception, Human–computer interaction
References
- [서평]Computer Graphics : Principles and Practice
- Mean Shift, Mode Seeking, and Clustering
- Visually Controlled Graphics
- Color gamut transform pairs
- Catching moving objects with snakes for motion tracking
- View-based and modular eigenspaces for face recognition
- Color-based tracking of heads and other mobile objects at video frame rates
- Computer vision for computer games
- Segmentation and tracking of faces in color images
- Tracking and learning graphs and pose on image sequences of faces
- Face locating and tracking for human-computer interaction
- Computer graphics: Principles and practice
- Pfinder: real-time tracking of the human body
- Robust analysis of feature spaces: color image segmentation
- Computer Vision
- Pfinder: real-time tracking of the human body
- Contour Tracking by Stochastic Propagation of Conditional Density
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- Robust identification of face landmarks in profile images
- Real-time Hand Locating by Monocular Vision
- Real-Time Human Tracking Using Skin Area and Modified Multi-CAMShift Algorithm
- People detection, tracking and re-identification through a video camera network. (Détection, suivi et ré-identification de personnes à travers un réseau de caméra vidéo)
- A general-purpose vision system for diverse robots
- On-board three-dimensional object tracking: Software and hardware solutions
- Visual motion estimation and tracking of rigid bodies by physical simulation
- Localisation et cartographie visuelles simultanées en milieu intérieur et en temps réel
- Towards A Robust and Real-time Face Detection and Tracking Framework
- Smart object, not smart environment : cooperative augmentation of smart objects using projector-camera systems
- On Real-Time Synthetic Primate Vision
- Robust Augmented Reality
- Automatic pedestrian detection and tracking with a multiple-cue max-margin framework
- Statiscal-based skin classifier for omni-directional images
- From local visual homing towards navigation of autonomous cleaning robots
- Contribution à la communication gestuelle dans les environnements virtuels collaboratifs
- Gesture and Speech for Video Content Navigation
- The Noldus database: Automated recognition of restaurant related activities for the restaurant of the future
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