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Computer Science - Image Processing | Person Re-Identification

Person Re-Identification

Gong, S., Cristani, M., Yan, S., Loy, C.C. (Eds.)

2014, XVIII, 445 p. 163 illus., 154 illus. in color.

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  • Presents a unified collection of state-of-the-art solutions to fundamental problems in computer vision
  • Examines a fast-growing topic of considerable interest to a broad audience
  • Contains contributions from an international selection of experts in the field

Re-identification offers a useful tool for non-invasive biometric validation, surveillance, and human-robot interaction in a broad range of applications from crowd traffic management to personalised healthcare.

This comprehensive volume is the first work of its kind dedicated to addressing the challenge of Person Re-Identification, presenting insights from an international selection of leading authorities in the field. Taking a strongly multidisciplinary approach, the text provides an in-depth discussion of recent developments and state-of-the-art methods drawn from the computer vision, pattern recognition and machine learning communities, embracing both fundamental research and practical applications.

Topics and features:

  • Introduces examples of robust feature representations, reviews salient feature weighting and selection mechanisms, and examines the benefits of semantic attributes
  • Describes how to segregate meaningful body parts from background clutter
  • Examines the use of 3D depth images, and contextual constraints derived from the visual appearance of a group
  • Reviews approaches to feature transfer function and distance metric learning, and discusses potential solutions to issues of data scalability and identity inference
  • Investigates the limitations of existing benchmark datasets, presents strategies for camera topology inference, and describes techniques for improving post-rank search efficiency
  • Explores the design rationale and implementation considerations of building a practical re-identification system

This timely collection will be of great interest to academics, industrial researchers and postgraduates involved in computer vision and machine learning, database image retrieval, big data mining, and search engines, as well as to developers keen to exploit this emerging technology for commercial applications.

Content Level » Research

Keywords » 3D Computer Vision - Active Learning - Attribute Learning - Behavioral Biometrics - Big Data Search - Context-Aware Recognition - Data Fusion - Data Mining - Distributed Camera Networks - Human Recognition - Image Retrieval - Multi-Camera Tracking - Multi-Instance Learning - People Detection - Person Re-Identification - Soft Biometrics - Transfer Learning - Video Content Analysis - Visual Surveillance

Related subjects » Artificial Intelligence - Database Management & Information Retrieval - HCI - Image Processing - Theoretical Computer Science

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