Mr. David Chen Profile

David Chen

Ph.D. Student

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Publications (8)

Proceedings Article | 15 October 2012 Paper

Improved coding for image feature location information

Radek Grzeszczuk, Sam Tsai, Mina Makar, David Chen, Vijay Chandrasekhar, Bernd Girod, Gabriel Takacs

Proceedings Volume 8499, 84991E (2012) https://doi.org/10.1117/12.935619

KEYWORDS: Quantization, Image compression, Image retrieval, Feature extraction, Visualization, Neodymium, Computer programming, Databases, Raster graphics, Image storage

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Proceedings Article | 15 October 2012 Paper

Rotation invariant fast features for large-scale recognition

Vijay Chandrasekhar, David Chen, Sam Tsai, Radek Grzeszczuk, Bernd Girod, Gabriel Takacs

Proceedings Volume 8499, 84991D (2012) https://doi.org/10.1117/12.945968

KEYWORDS: Detection and tracking algorithms, Databases, Sensors, Image retrieval, Feature extraction, Video, Image filtering, Image processing, Augmented reality, Buildings

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Proceedings Article | 24 September 2011 Paper

Compressing a set of CHoG features

David Chen, Sam Tsai, Gabriel Takacs, Vijay Chandrasekhar, Yuriy Reznik, Bernd Girod

Proceedings Volume 8135, 813517 (2011) https://doi.org/10.1117/12.895431

KEYWORDS: Feature extraction, Computer programming, Binary data, Image transmission, Visualization, Image compression, Image retrieval, Mobile devices, Databases, Digital imaging

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Proceedings Article | 8 September 2010 Paper

Low-cost asset tracking using location-aware camera phones

Cheng-Hsin Hsu, Kyu-Han Kim, Jatinder Pal Singh, David Chen, Bernd Girod, Sam Tsai

Proceedings Volume 7798, 77980R (2010) https://doi.org/10.1117/12.862426

KEYWORDS: Spine, Image segmentation, Databases, Sensors, Visualization, Image analysis, Cameras, Optical character recognition, Feature extraction, Detection and tracking algorithms

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Maintaining an accurate and up-to-date inventory of one's assets is a labor-intensive, tedious, and costly operation. To ease this difficult but important task, we design and implement a mobile asset tracking system for automatically generating an inventory by snapping photos of the assets with a smartphone. Since smartphones are becoming ubiquitous, construction and deployment of our inventory management solution is simple and costeffective. Automatic asset recognition is achieved by first segmenting individual assets out of the query photo and then performing bag-of-visual-features (BoVF) image matching on the segmented regions. The smartphone's sensor readings, such as digital compass and accelerometer measurements, can be used to determine the location of each asset, and this location information is stored in the inventory for each recognized asset. As a special case study, we demonstrate a mobile book tracking system, where users snap photos of books stacked on bookshelves to generate a location-aware book inventory. It is shown that segmenting the book spines is very important for accurate feature-based image matching into a database of book spines. Segmentation also provides the exact orientation of each book spine, so more discriminative upright local features can be employed for improved recognition. This system's mobile client has been implemented for smartphones running the Symbian or Android operating systems. The client enables a user to snap a picture of a bookshelf and to subsequently view the recognized spines in the smartphone's viewfinder. Two different pose estimates, one from BoVF geometric matching and the other from segmentation boundaries, are both utilized to accurately draw the boundary of each spine in the viewfinder for easy visualization. The BoVF representation also allows matching each photo of a bookshelf rack against a photo of the entire bookshelf, and the resulting feature matches are used in conjunction with the smartphone's orientation sensors to determine the exact location of each book.

Proceedings Article | 8 September 2010 Paper

Permutable descriptors for orientation-invariant image matching

Radek Grzeszczuk, Bernd Girod, Vijay Chandrasekhar, Gabriel Takacs, Huizhong Chen, David Chen, Sam Tsai

Proceedings Volume 7798, 77980M (2010) https://doi.org/10.1117/12.863993

KEYWORDS: Spatial resolution, Databases, Error analysis, Receivers, Augmented reality, Wavelets, Algorithm development, Video, Feature extraction, Distance measurement

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Proceedings Article | 8 September 2010 Paper

Fast quantization and matching of histogram-based image features

David Chen, Sam Tsai, Vijay Chandrasekhar, Bernd Girod, Yuriy Reznik, Gabriel Takacs

Proceedings Volume 7798, 77980L (2010) https://doi.org/10.1117/12.862362

KEYWORDS: Quantization, Image compression, Distance measurement, Reconstruction algorithms, Databases, Binary data, Computer programming, Receivers, Visualization, Cell phones

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Proceedings Article | 19 January 2009 Paper

Transform coding of image feature descriptors

Gabriel Takacs, Vijay Chandrasekhar, Jatinder Singh, Sam Tsai, David Chen, Bernd Girod

Proceedings Volume 7257, 725710 (2009) https://doi.org/10.1117/12.805982

KEYWORDS: Image compression, Distortion, Databases, Image retrieval, Quantization, Feature extraction, Computer programming, Image storage, Image transmission, Binary data

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Proceedings Article | 19 January 2009 Paper

Robust image retrieval using multiview scalable vocabulary trees

Bernd Girod, Jatinder Singh, David Chen, Gabriel Takacs, Vijay Chandrasekhar, Sam Tsai

Proceedings Volume 7257, 72570V (2009) https://doi.org/10.1117/12.805606

KEYWORDS: Distortion, Databases, Feature extraction, Image retrieval, Silicon, Sensors, Image resolution, Content based image retrieval, Image classification, Image segmentation

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Showing 5 of 8 publications

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