Segmentation and content-based watermarking for color image and image region indexing and retrieval
EURASIP Journal on Applied Signal Processing - Image analysis for multimedia interactive services - part I
A Wavelet-Based Preprocessing for Moving Object Segmentation in Video Sequences
WAA '01 Proceedings of the Second International Conference on Wavelet Analysis and Its Applications
Unsupervised video object segmentation and tracking based on new edge features
Pattern Recognition Letters
Segmentation and content-based watermarking for color image and image region indexing and retrieval
EURASIP Journal on Applied Signal Processing
Region-based image retrieval using an object ontology and relevance feedback
EURASIP Journal on Applied Signal Processing
Applying the multi-category learning to multiple video object extraction
Pattern Recognition
SEGMENTATION OF MULTIPLE HUMAN OBJECTS IN VIDEO SEQUENCES
Applied Artificial Intelligence
Temporal segmentation based on video coding
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Immersive video conferencing architecture using game engine technology
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part II
Moving object detection based on a new level set algorithm using directional speed function
ICAT'06 Proceedings of the 16th international conference on Advances in Artificial Reality and Tele-Existence
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A procedure is described for the segmentation, content-based coding, and visualization of videoconference image sequences. First, image sequence analysis is used to estimate the shape and motion parameters of the person facing the camera. A spatiotemporal filter, taking into account the intensity differences between consequent frames, is applied, in order to separate the moving person from the static background. The foreground is segmented in a number of regions in order to identify the face. For this purpose, we propose the novel procedure of K-means with connectivity constraint algorithm as a general segmentation algorithm combining several types of information including intensity, motion and compactness. In this algorithm, the use of spatiotemporal regions is introduced since a number of frames are analyzed simultaneously and as a result, the same region is present in consequent frames. Based on this information, a 3-D ellipsoid is adapted to the person's face using an efficient and robust algorithm. The rigid 3-D motion is estimated next using a least median of squares approach, Finally, a virtual reality modeling language (VRML) file is created containing all the above information; this file may be viewed by using any VRML 2.0 compliant browser