A New Mesh-Based Temporal-Spatial Segmentation for Image Sequence
COMPSAC '00 24th International Computer Software and Applications Conference
Non-sequential multiscale content-based video decomposition
Signal Processing - Special section on content-based image and video retrieval
Proceedings of the international workshop on Workshop on multimedia information retrieval
Multimedia Tools and Applications
Mobile face detection and tracking for media streaming applications
International Journal of Wireless and Mobile Computing
IEEE Transactions on Image Processing
Visual attention guided bit allocation in video compression
Image and Vision Computing
A region-based rate-control scheme using inter-layer information for H.264/SVC
Journal of Visual Communication and Image Representation
Event-driven video adaptation: A powerful tool for industrial video supervision
Multimedia Tools and Applications
| Hi-index | 0.00 |
An adaptive algorithm for extracting foreground objects from background in videophone or videoconference applications is presented. The algorithm uses a neural network architecture that classifies the video frames in regions of interest (ROI) and non-ROI areas, also being able to automatically adapt its performance to scene changes. The algorithm is incorporated in motion-compensated discrete cosine transform (MC-DCT)-based coding schemes, allocating more bits to ROI than to non-ROI areas. Simulation results are presented, using the Claire and Trevor sequences, which show reconstructed images of better quality, as well as signal-to-noise ratio improvements of about 1.4 dB, compared to those achieved by standard MC-DCT encoders