Industrial Technology Research Institute

Jiann-Jone Chen

Cheng-Yi Liu

I-Yen Chen

Hua-Yi Lin

Jiann-Yu Wen

Jau-Fu Liu

Kuo-Huang Chung

Chen-Chin Chiang

A method and a system for transmitting a live media stream to a plurality of nodes under a multicast tree in peer-to-peer (P2P) networks are provided. First, the reliability of each node is calculated according to a number of child nodes that can be supported by the node and an accumulated on-line time of the node. According to the number of child nodes and the reliability of each node, the nodes are rearranged in a database to establish an ideal reliable multicast tree. Finally, according to the reliability of each node, a location of each node in the multicast tree is practically adapted in sequence in a descending order, and a relative delay between nodes is weighted and compared, so a level difference between the adapted level of the node in the multicast tree and the level of the node in the ideal reliable multicast tree is the smallest.

Method and system for transmitting live media streaming in peer-to-peer networks

A background removal apparatus comprises a color normalization module that normalizes an original image, and an image segmentation module that segments the normalized image into several segmented regions. A background mesh generation module simulates the variation of pixel colors in background and generates an interpolated background mesh. A comparison module compares the normalized image and the interpolated background mesh to form a background mask by extracting the coherent regions between them. A refinement module uses a refined rule to determine a final background mask, and a background removal module through which a pure foreground image is obtained. The apparatus combines the efficiency of both color and spatial clustering, and improves the capabilities of current image segmentation method to perform background removal.

Apparatus and method for removing background on visual

An image retrieval system for retrieving image similarities from a database is proposed. The image retrieval system uses a universal query mechanism (UQM) to locate statistically silent common features among sample query images from different feature sets. The UQM also adjusts the weight factor for each feature to meet a user's query demand.

Content-based similarity retrieval system for image data

Growing community of inventors

Taipei, Taiwan

Jiann-Jone Chen