Vector quantization and signal compression
Vector quantization and signal compression
Performance of optical flow techniques
International Journal of Computer Vision
Human motion analysis: a review
Computer Vision and Image Understanding
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Accuracy and Stability of Numerical Algorithms
Accuracy and Stability of Numerical Algorithms
Real-time American Sign Language recognition from video using hidden Markov models
ISCV '95 Proceedings of the International Symposium on Computer Vision
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
A Non-Iterative Greedy Algorithm for Multi-frame Point Correspondence
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
MIThril 2003: Applications and Architecture
ISWC '03 Proceedings of the 7th IEEE International Symposium on Wearable Computers
A multimodal learning interface for grounding spoken language in sensory perceptions
Proceedings of the 5th international conference on Multimodal interfaces
Space-Time Behavior Based Correlation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Vision-based hand pose estimation: A review
Computer Vision and Image Understanding
Memory representations in natural tasks
Journal of Cognitive Neuroscience
Efficient Visual Search of Videos Cast as Text Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Attentive interfaces for users with disabilities: eye gaze for intention and uncertainty estimation
Universal Access in the Information Society - Special Issue: Communication by Gaze Interaction
Guest Editorial: State of the Art in Image- and Video-Based Human Pose and Motion Estimation
International Journal of Computer Vision
A survey on vision-based human action recognition
Image and Vision Computing
Action recognition with semi-global characteristics and hidden Markov models
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
SenseCam: a retrospective memory aid
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Object-based activity recognition with heterogeneous sensors on wrist
Pervasive'10 Proceedings of the 8th international conference on Pervasive Computing
FaceMouse: a human-computer interface for tetraplegic people
ECCV'06 Proceedings of the 2006 international conference on Computer Vision in Human-Computer Interaction
Machine Recognition of Human Activities: A Survey
IEEE Transactions on Circuits and Systems for Video Technology
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Human beings are very skillful at reaching for and grasping objects under multiple conditions, even when faced with an object's wide variety of positions, locations, structures and orientations. This natural ability, controlled by the human brain, is called eye-hand coordination. To understand this behavior it is necessary to study both eye and hand movements simultaneously. This paper proposes a novel approach to detect grasping movements by means of computer vision techniques. This solution fuses two viewpoints, one viewpoint which is obtained from an eye-tracker capturing the user's perspective and a second viewpoint which is captured by a wearable camera attached to a user's wrist. Utilizing information from these two viewpoints it is possible to characterize multiple hand movements in conjunction with eye-gaze movements through a Hidden-Markov Model framework. This paper shows that combining these two sources makes it possible to detect hand gestures using only the objects contained in the scene even without markers on the surface of the objects. In addition, it is possible to detect which is the desired object before the user can actually grasp said object.