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964
Person Re-identification by Attributes
"... Visually identifying a target individual reliably in a crowded environment observed by a distributed camera network is critical to a variety of tasks in managing business information, border control, and crime prevention. Automatic re-identification of a human candidate from public space CCTV video ..."
Abstract
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Cited by 21 (6 self)
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to describe people. Specifically, the model learns an attribute-centric, parts-based feature representation. This differs from and complements existing low-level features for re-identification that rely purely on bottom-up statistics for feature selection, which are limited in discriminating and identifying
Features of similarity.
- Psychological Review
, 1977
"... Similarity plays a fundamental role in theories of knowledge and behavior. It serves as an organizing principle by which individuals classify objects, form concepts, and make generalizations. Indeed, the concept of similarity is ubiquitous in psychological theory. It underlies the accounts of stimu ..."
Abstract
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Cited by 1455 (2 self)
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and metric assumptions are open to question. It has been argued by many authors that dimensional representations are appropriate for certain stimuli (e.g., colors, tones) but not for others. It seems more appropriate to represent faces, countries, or personalities in terms of many qualitative features than
Relaxed pairwise learned metric for person re-identification
- In ECCV
, 2012
"... Abstract. Matching persons across non-overlapping cameras is a rather challenging task. Thus, successful methods often build on complex feature representations or sophisticated learners. A recent trend to tackle this problem is to use metric learning to find a suitable space for matching samples fro ..."
Abstract
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Cited by 55 (2 self)
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Abstract. Matching persons across non-overlapping cameras is a rather challenging task. Thus, successful methods often build on complex feature representations or sophisticated learners. A recent trend to tackle this problem is to use metric learning to find a suitable space for matching samples
A Trainable System for Object Detection
, 2000
"... This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes an object class in terms of an overcomplete dictionary of local, oriented, multiscale intensity differences between adj ..."
Abstract
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Cited by 344 (8 self)
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tasks using the same architecture. In addition, we quantify how the representation affects detection performance by considering several alternate representations including pixels and principal components. We also describe a real-time application of our person detection system as part of a driver
Person re-identification by probabilistic relative distance comparison
- In IEEE Conference on Computer Vision and Pattern Recognition
, 2011
"... Matching people across non-overlapping camera views, known as person re-identification, is challenging due to the lack of spatial and temporal constraints and large visual appearance changes caused by variations in view angle, lighting, background clutter and occlusion. To address these challenges, ..."
Abstract
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Cited by 63 (10 self)
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to formulate person re-identification as a distance learning problem, which aims to learn the optimal distance that can maximises matching accuracy regardless the choice of representation. To that end, we introduce a novel Probabilistic Relative Distance Comparison (PRDC) model, which differs from most
CHENG et al.: CUSTOM PICTORIAL STRUCTURES FOR RE-IDENTIFICATION 1 Custom Pictorial Structures for Re-identification
"... We propose a novel methodology for re-identification, based on Pictorial Structures (PS). Whenever face or other biometric information is missing, humans recognize an individual by selectively focusing on the body parts, looking for part-to-part correspondences. We want to take inspiration from this ..."
Abstract
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Cited by 1 (0 self)
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on that specific person, leading to what we call a Custom Pictorial Structure (CPS). CPS learns the appearance of an individual, improving the localization of its parts, thus obtaining more reliable visual characteristics for re-identification. It is based on the statistical learning of pixel attributes collected
T.: The re-identification challenge
- In: Person Re-Identification
, 2014
"... Abstract For making sense of the vast quantity of visual data generated by the rapid expansion of large scale distributed multi-camera systems, automated per-son re-identification is essential. However, it poses a significant challenge to com-puter vision systems. Fundamentally, person re-identifica ..."
Abstract
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Cited by 6 (5 self)
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the discovery of, and reasoning about, individual-specific long-term structured activities and behaviours. Solving the person re-identification problem is inherently challenging but promises enormous potential for a wide range of practical applications, ranging from security and surveillance to retail
DENSE APPEARANCE MODELING AND EFFICIENT LEARNING OF CAMERA TRANSITIONS FOR PERSON RE-IDENTIFICATION
"... One central task in many visual surveillance scenarios is person re-identification, i.e., recognizing an individual person across a network of spatially disjoint cameras. Most successful recognition approaches are either based on direct modeling of the human appearance or on machine learning. In thi ..."
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One central task in many visual surveillance scenarios is person re-identification, i.e., recognizing an individual person across a network of spatially disjoint cameras. Most successful recognition approaches are either based on direct modeling of the human appearance or on machine learning
Person Re-identification with Correspondence Structure Learning
"... This paper addresses the problem of handling spatial misalignments due to camera-view changes or human-pose variations in person re-identification. We first introduce a boosting-based approach to learn a correspondence struc-ture which indicates the patch-wise matching probabilities between images f ..."
Abstract
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Cited by 1 (1 self)
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This paper addresses the problem of handling spatial misalignments due to camera-view changes or human-pose variations in person re-identification. We first introduce a boosting-based approach to learn a correspondence struc-ture which indicates the patch-wise matching probabilities between images
H.: Person re-identification by descriptive and discriminative classification
- In: Proc. SCIA. (2011
"... Abstract. Person re-identification, i.e., recognizing a single person across spatially disjoint cameras, is an important task in visual surveillance. Existing approaches either try to find a suitable description of the appearance or learn a discriminative model. Since these different representationa ..."
Abstract
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Cited by 44 (5 self)
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Abstract. Person re-identification, i.e., recognizing a single person across spatially disjoint cameras, is an important task in visual surveillance. Existing approaches either try to find a suitable description of the appearance or learn a discriminative model. Since these different
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964
