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Results 11 - 20
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21,750
Computer Vision Face Tracking For Use in a Perceptual User Interface
, 1998
"... As a first step towards a perceptual user interface, a computer vision color tracking algorithm is developed and applied towards tracking human faces. Computer vision algorithms that are intended to form part of a perceptual user interface must be fast and efficient. They must be able to track in re ..."
Abstract
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Cited by 357 (4 self)
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As a first step towards a perceptual user interface, a computer vision color tracking algorithm is developed and applied towards tracking human faces. Computer vision algorithms that are intended to form part of a perceptual user interface must be fast and efficient. They must be able to track
In Computational Vision
, 1989
"... This paper provides an overview of ongoing research in the GRASP laboratory which focuses on the general problem of symbolic inference in computational vision. In this report we describe a conceptual framework for this research, and describe our current research programs in the component areas which ..."
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This paper provides an overview of ongoing research in the GRASP laboratory which focuses on the general problem of symbolic inference in computational vision. In this report we describe a conceptual framework for this research, and describe our current research programs in the component areas
Computer Vision Research at the Computational Vision
"... Abstract. The development of research in computer vision in a developing country is a challenging task. Factors such as low research funds, low trust from local companies and governments, and small number of qualified researchers complicates the development of strong, local research groups. In this ..."
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Abstract. The development of research in computer vision in a developing country is a challenging task. Factors such as low research funds, low trust from local companies and governments, and small number of qualified researchers complicates the development of strong, local research groups
Computer Vision
"... 3. Biological visual mechanisms, from retina to primary cortex. 4. Mathematical operations for extracting structure from images. 5. Edge detection operators; the Laplacian and its zero-crossings. 6. Multi-resolution. Active Contours. Wavelets as visual primitives. 7. Higher brain visual mechanisms; ..."
Computer Vision
"... 3. Biological visual mechanisms, from retina to primary cortex. 4. Mathematical operations for extracting structure from images. 5. Edge detection operators; the Laplacian and its zero-crossings. 6. Multi-resolution. Active Contours. Wavelets as primitives; SIFT. 7. Higher brain visual mechanisms; s ..."
Computer Vision
"... 3. Biological visual mechanisms, from retina to primary cortex. 4. Mathematical operations for extracting structure from images. 5. Edge detection operators; the Laplacian and its zero-crossings. 6. Scale-space; multi-resolution. Wavelets as visual primitives. 7. Higher brain visual mechanisms; stre ..."
Computer Vision
"... vision. 3. Mathematical operations for extracting structure from images. 4. Edge detection operators; the Laplacian and its zero-crossings. 5. Multi-scale feature detection and matching. 6. Texture, colour, stereo, and motion descriptors. Disambiguation. 7. Lambertian and specular surface properties ..."
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and Content based image retrieval. 12. Face detection, face recognition, and facial interpretation. Syllabus Aims The aims of this course are to introduce the principles, models and applications of computer vision. The course will cover: image formation, structure, and coding; edge and feature
Robust parameter estimation in computer vision
- SIAM Reviews
, 1999
"... Abstract. Estimation techniques in computer vision applications must estimate accurate model parameters despite small-scale noise in the data, occasional large-scale measurement errors (outliers), and measurements from multiple populations in the same data set. Increasingly, robust estimation techni ..."
Abstract
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Cited by 164 (10 self)
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Abstract. Estimation techniques in computer vision applications must estimate accurate model parameters despite small-scale noise in the data, occasional large-scale measurement errors (outliers), and measurements from multiple populations in the same data set. Increasingly, robust estimation
Computational Vision
"... ‡ Last time The previous lecture provided an overview of we are going and the approach. We'd like to understand how we "know what is where just by looking", how our brains enable us to infer "states of the world", such as scene and object parameters, and how vision supports ..."
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‡ Last time The previous lecture provided an overview of we are going and the approach. We'd like to understand how we "know what is where just by looking", how our brains enable us to infer "states of the world", such as scene and object parameters, and how vision supports
Results 11 - 20
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21,750
