Single-camera automatic landmarking for people recognition with an ensemble of regression trees
Document title: Single-camera automatic landmarking for people recognition with an ensemble of regression trees
Journal: Computación y sistemas
Database: PERIÓDICA
System number: 000408045
ISSN: 1405-5546
Authors: 1
1
Institutions: 1Universidad Politécnica de Cataluña, Barcelona. España
Year:
Season: Ene-Mar
Volumen: 20
Number: 1
Pages: 19-28
Country: México
Language: Inglés
Document type: Artículo
Approach: Aplicado
English abstract Active Appearance Model (AAM) is a computer vision procedure for statistical matching of object shape and appearance between images. A main drawback in this technique comes from the construction of the shape mesh. Since landmarks must be manually placed when training shapes, AAM is a very time consuming procedure and it cannot be automatically applied on new objects observed in the images. An approach for automatic landmarking of body shapes on still images for AAM training is introduced in this paper. Several works exist applying automatic landmarking on faces or body joints. Here, we explore the possibility to extend one of these methods to full body contours and demonstrate it is a plausible approach in terms of accuracy and speed measures in experimentation. Our proposal represents a new research line in human body pose tracking with a single-view camera. Hence, implementation in real-time would lead to people being recognized by robots endowed with minimal vision resources, like a webcam, in human-robot interaction tasks
Disciplines: Ciencias de la computación,
Matemáticas
Keyword: Inteligencia artificial,
Procesamiento de datos,
Matemáticas aplicadas,
Visión por computadora,
Reconocimiento de patrones,
Reconocimiento de imágenes,
Apareamiento,
Modelo de aspecto activo,
Modelos estadísticos,
Cuerpo humano
Keyword: Computer science,
Mathematics,
Artificial intelligence,
Data processing,
Applied mathematics,
Computer vision,
Pattern recognition,
Image recognition,
Matching,
Active appearance model,
Statistical models,
Human body
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