Mr. Christopher R. Brown Profile

Christopher R. Brown

Engineer at L-3 Communications

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Publications (5)

Proceedings Article | 14 April 2003 Paper

High-performance architecture for color error diffusion

Christopher Brown, Andreas Savakis

Proceedings Volume 5012, (2003) https://doi.org/10.1117/12.477498

KEYWORDS: Image processing, Diffusion, Clocks, Data processing, Field programmable gate arrays, Signal processing, Process control, Data storage, Computer architecture, Image storage

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Proceedings Article | 7 December 2001 Paper

Document processing for automatic color form dropout

Andreas Savakis, Christopher Brown

Proceedings Volume 4472, (2001) https://doi.org/10.1117/12.449788

KEYWORDS: RGB color model, Image processing, Optical filters, Field programmable gate arrays, Tolerancing, Optical spheres, Clocks, Matrix multiplication, Scanners, Optical character recognition

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Proceedings Article | 28 May 2001 Paper

Augmented-reality visualization of brain structures with stereo and kinetic depth cues: system description and initial evaluation with head phantom

Calvin Maurer, Frank Sauer, Bo Hu, Benedicte Bascle, Bernhard Geiger, Fabian Wenzel, Filippo Recchi, Torsten Rohlfing, Christopher Brown, Robert Bakos, Robert Maciunas, Ali Bani-Hashemi

Proceedings Volume 4319, (2001) https://doi.org/10.1117/12.428086

KEYWORDS: Cameras, Head, Video, Visualization, Computed tomography, Head-mounted displays, Brain, Image segmentation, Surgery, Navigation systems

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We are developing a video see-through head-mounted display (HMD) augmented reality (AR) system for image-guided neurosurgical planning and navigation. The surgeon wears a HMD that presents him with the augmented stereo view. The HMD is custom fitted with two miniature color video cameras that capture a stereo view of the real-world scene. We are concentrating specifically at this point on cranial neurosurgery, so the images will be of the patient's head. A third video camera, operating in the near infrared, is also attached to the HMD and is used for head tracking. The pose (i.e., position and orientation) of the HMD is used to determine where to overlay anatomic structures segmented from preoperative tomographic images (e.g., CT, MR) on the intraoperative video images. Two SGI 540 Visual Workstation computers process the three video streams and render the augmented stereo views for display on the HMD. The AR system operates in real time at 30 frames/sec with a temporal latency of about three frames (100 ms) and zero relative lag between the virtual objects and the real-world scene. For an initial evaluation of the system, we created AR images using a head phantom with actual internal anatomic structures (segmented from CT and MR scans of a patient) realistically positioned inside the phantom. When using shaded renderings, many users had difficulty appreciating overlaid brain structures as being inside the head. When using wire frames, and texture-mapped dot patterns, most users correctly visualized brain anatomy as being internal and could generally appreciate spatial relationships among various objects. The 3D perception of these structures is based on both stereoscopic depth cues and kinetic depth cues, with the user looking at the head phantom from varying positions. The perception of the augmented visualization is natural and convincing. The brain structures appear rigidly anchored in the head, manifesting little or no apparent swimming or jitter. The initial evaluation of the system is encouraging, and we believe that AR visualization might become an important tool for image-guided neurosurgical planning and navigation.

Proceedings Article | 22 September 1997 Paper

Dynamic Bayes net approach to multimodal sensor fusion

Amit Singhal, Christopher Brown

Proceedings Volume 3209, (1997) https://doi.org/10.1117/12.287628

KEYWORDS: Sensors, Sensor fusion, Mobile robots, Sensor performance, Environmental sensing

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Proceedings Article | 31 January 1995 Paper

Bayes nets for selective perception and data fusion

Christopher Brown, Mauricio Marengoni, George Kardaras

Proceedings Volume 2368, (1995) https://doi.org/10.1117/12.200788

KEYWORDS: Visualization, Sensors, Image processing, Cameras, Image sensors, Visual process modeling, Control systems, Image analysis, Data fusion, Systems modeling

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