Dr. Liang-Chi Hsieh is a researcher dedicated to large-scale multimedia system design and algorithm. His research topics cover image automatic annotation, multimedia indexing and search, large-scale multimedia data processing. He received Computer Science Ph.D. degree from Graduate Institute of Networking and Multimedia, National Taiwan University. He is also an experienced and active programmer dedicated to Open Source Software. He actively participates in Free and Open Source Software communities by code contribution, articles translation. He also helps translate some articles related to open source and Creative Commons from English to Chinese.

  • Lire-based image search system: Based on Lucene-based Lire project. This system uses sparse visual-word as image features to build index for image collection. It can be used to support real-time content-based image retrieval system. In experiments it is capable to search on half of million images (1 million visual-word) within few seconds with index stored on quite slow NFS. It could be used to prove that it is possible to achieve such system with current open source technologies without those too complicated mess in some papers.
  • ANN-based CBIR server: An ANN-based (Approximate Nearest Neighbor) CBIR (content-based image retrieval) server with HTTP-based interface.
  • ZhuYinIME (注音輸入法): A Chinese input method application for Android platform.
  • Terminal application for Android: A fork of rTerm application on Android with soft input and view-zoom support.
  • PHP extension for Random Walk with Restart(RWR): A PHP extension for RWR algorithm. Optimised with BLAS and OpenMP. It can be used to support online search result reranking. We use it in online image clustering project.
  • Liang-Chi Hsieh, Ching-Wei Lee, Tzu-Hsuan Chiu, Winston Hsu, "Live Semantic Sport Highlight Detection Based on Analyzing Tweets of Twitter," ICME 2012.
  • Liang-Chi Hsieh, Guan-Long Wu, Wen-Yu Lee, Winston Hsu, "TWO-STAGE SPARSE GRAPH CONSTRUCTION USING MINHASH ON MAPREDUCE," ICASSP 2012.
  • Wen-Yu Lee, Liang-Chi Hsieh, Guan-Long Wu, Winston Hsu, "Graph-based Semi-Supervised Learning with Multi-Modality Propagation for Large-Scale Image Datasets," Journal of Visual Communication and Image Representation, 2012.
  • Yen-Ta Huang, Liang-Chi Hsieh, Kuan-Ting Chen, Winston H. Hsu, "Detecting Viewing Directions to Landmarks for Recommendation by Large-scale User-contributed Photos," ACM Multimedia 2012.
  • Wu, Guan-Long and Su, Yu-Chuan and Chiu, Tzu-Hsuan and Hsieh, Liang-Chi and Hsu, Winston H., "Scalable mobile video question-answering system with locally aggregated descriptors and random projection," Grand Challenge, ACM Multimedia 2011.
  • Wenyu Lee, Guan-Long Wu, Liang-Chi Hsieh, Winston Hsu, “Multi-layer Graph-Based Semi-supervised Learning for Large-Scale Image Datasets using MapReduce,” SIGIR 2011. [Poster]
  • Yen-Ta Huang, Liang-Chi Hsieh, An-Jung Cheng, Winston Hsu, “Region-Based Landmark Discovery by Crowdsourcing Geo-Referenced Photos,” SIGIR 2011. [Poster]
  • Sheng-Yuan Wang, Wei-Shing Liao, Liang-Chi Hsieh, Yan-Ying Chen, Winston H. Hsu, ”Learning by Expansion: Exploiting Social Media for Image Classification with Few Training Examples,” Neurocomputing, 2011
  • Liang-Chi Hsieh, Winston H. Hsu, “SEARCH-BASED AUTOMATIC IMAGE ANNOTATION VIA FLICKR PHOTOS USING TAG EXPANSION,” ICASSP 2010. [Poster]
  • Liang-Chi Hsieh, Kuan-Ting Chen, Chien-Hsing Chiang, Yi-Hsuan Yang, Guan-Long Wu, Chun-Sung Ferng, Hsiu-Wen Hsueh, Charng-Rurng Tsai, Winston H. Hsu, “Canonical Image Selection and Efficient Image Graph Construction for Large-Scale Flickr Photos,” Grand Challenge in ACM Multimedia 2009. (Demo video)
  • Tsung Teng Chen, Liang Chi Hsieh, “The Visualization of Relatedness”, IV 2008: 415-420.
  • Tsung Teng Chen, Liang Chi Hsieh, “On Visualization of Cocitation Networks”, IV 2007: 470-475.
  • Tsung Teng Chen, Liang Chi Hsieh, “Uncovering the Latent Underlying Domains of a Research Field: Knowledge Visualization Revealed”, IV 2006: 252-256.
  • Tsung Teng Chen, Liang Qi Xie, “Identifying Critical Focuses in Research Domains”, IV 2005: 135-142.