Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color-Based Tracking of Heads and Other Mobile Objects at Video Frame Rates
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Interpreting Face Images Using Active Appearance Models
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Detecting Pedestrians Using Patterns of Motion and Appearance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Counting Crowded Moving Objects
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Unsupervised Bayesian Detection of Independent Motion in Crowds
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Measure Locally, Reason Globally: Occlusion-sensitive Articulated Pose Estimation
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
ACM Computing Surveys (CSUR)
Tracking People by Learning Their Appearance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Human Detection by Boosting Histograms of Oriented Gradients
ICIG '07 Proceedings of the Fourth International Conference on Image and Graphics
BM3E: Discriminative Density Propagation for Visual Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rapid and robust human detection and tracking based on omega-shape features
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Unsupervised Learning of Activities in Video Using Scene Context
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
An efficient face location using integrated feature space
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
A Bayesian discriminating features method for face detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic Reconfiguration Based on Goal-Scenario by Adaptation Strategy
Wireless Personal Communications: An International Journal
Bio-Interactive Healthcare Service System Using Lifelog Based Context Computing
Wireless Personal Communications: An International Journal
Home Health Gateway Based Healthcare Services Through U-Health Platform
Wireless Personal Communications: An International Journal
Interactive Design Recommendation Using Sensor Based Smart Wear and Weather WebBot
Wireless Personal Communications: An International Journal
Development of head detection and tracking systems for visual surveillance
Personal and Ubiquitous Computing
Recent trends on mobile computing and future networks
Personal and Ubiquitous Computing
Hi-index | 0.00 |
This study propose a system of extracting and tracking objects for a multimedia system and addresses how to extract the head feature from an object area. It is observed in images taken from real-time records like a video, there is always a variance in human behavior, such as the position, size, etc. of the person being tracked or recorded. This study discusses how to extract and track multiple objects based on context as opposed to a single object. Via cascade extraction, the proposed system allows tracking of more than one human at a time. For this process, an extraction method based on internal and external contexts, which defines features to distinguish a human, is proposed. The proposed method defines shapes of shoulder and head area to recognize the head-shape of a human, and creates an extractor according to its edge information and geometrical shapes context. In this paper, humans in images are extracted and recognized using contexts and profiles. The proposed method is compared with a single face detector system and it shows better performance in terms of precision and speed. This trace information can be applied in safety care system. Extractions can be improved by validating the image using a context based detector when there are duplicated images.