INDUSTRY ACADEMIC COOPERATION FOUNDATION OF KYUNG HEE UNIVERSITY Patent applications |
Patent application number | Title | Published |
20110077919 | METHOD OF RECOGNIZING ACTIVITY ON BASIS OF SEMI-MARKOV CONDITIONAL RANDOM FIELD MODEL - A method of recognizing an activity on the basis of a semi-Markov conditional random field (CRF) model is provided. The method includes segmenting an input signal measured by an accelerometer to output frame sequences, extracting training feature vectors from the frame sequences, building a codebook containing kernel vectors from the training feature vectors; quantizing vector sequences into discrete symbol sequences, using linear chain semi-Markov CRF model to compute the likelihood of a label given its corresponding symbol sequence. | 03-31-2011 |
20100231688 | METHOD AND APPARATUS FOR BLOCK-BASED DEPTH MAP CODING AND 3D VIDEO CODING METHOD USING THE SAME - Provided are a block-based depth map coding method and apparatus and a 3D video coding method using the same. The depth map coding method decodes a received bitstream in units of blocks of a predetermined size using a bitplane decoding method to reconstruct a depth map. For example, the depth map coding method may decode the bitstream in units of blocks using the bitplane decoding method or an existing Discrete Cosine Transform (DCT)-based decoding method adaptively according to decoded coding mode information. The bitplane decoding method may include adaptively performing XOR operation in units of bitplane blocks. For example, a determination on whether or not to perform XOR operation may be done in units of bitplane blocks according to the decoded value of XOR operation information contained in the bitstream. | 09-16-2010 |
20090328148 | METHOD OF TRUST MANAGEMENT IN WIRELESS SENSOR NETWORKS - The present invention relates to Group-based trust management scheme (GTMS) of wireless sensor networks. GTMS evaluates the trust of a group of sensor nodes in contrast to traditional trust management schemes that always focused on trust values of individual nodes. This approach gives us the benefit of requiring less memory to store trust records at each sensor node in the network. It uses the clustering attributes of wireless sensor networks that drastically reduce the cost associated with trust evaluation of distant nodes. Uniquely it provides not only a mechanism to detect malicious or faulty nodes, but also provides some degree of a prevention mechanism. | 12-31-2009 |
20090046910 | Method for enhancing blood vessels in angiography images - Disclosed is a method for enhancing blood vessels in angiography images. The method incorporates the use of linear directional features present in an image, extracted by a Directional Filter Bank, to obtain more precise Hessian analysis in noisy environment and thus can correctly reveal small and thin vessels. Also, the directional image decomposition helps to avoid junction suppression, which in turn, yields continuous vessel tree. | 02-19-2009 |
20090046678 | Method for predicting the mobility in mobile ad hoc networks - Disclosed are methods for determining the neighborhood local view of a mobile node in time which can facilitate the forwarding decision in the design of network protocols. In conventional mobile ad hoc networks nodes set up local topology view based on periodical received “Hello” messages. The conventional method is replaced with proactive and adaptive methods of predicting locations of nodes based on preserved historical information extracted from received “Hello” messages and constructing neighborhood view by aggregating predicted locations. This method is useful for providing updated and consistent topology local view that a network communication employs to determine optimal forward decisions and improve communication performance. | 02-19-2009 |