Results 41 to 50 of about 1,229,322 (315)
A New Model for Person Reidentification Using Deep CNN and Autoencoders [PDF]
Person re-identification (re-id) is one of the most critical and challenging topics in image processing and artificial intelligence. In general, person re-identification means that a person seen in the field of view of one camera can be found and tracked
A. Sezavar, H. Farsi, S. Mohamadzadeh
doaj +1 more source
Relation Network for Person Re-Identification
Person re-identification (reID) aims at retrieving an image of the person of interest from a set of images typically captured by multiple cameras. Recent reID methods have shown that exploiting local features describing body parts, together with a global feature of a person image itself, gives robust feature representations, even in the case of missing
Bumsub Ham, Hyunjong Park
openaire +3 more sources
Person Re-Identification via Attention Pyramid [PDF]
In this paper, we propose an attention pyramid method for person re-identification. Unlike conventional attention-based methods which only learn a global attention map, our attention pyramid exploits the attention regions in a multi-scale manner because human attention varies with different scales.
Guangyi Chen+4 more
openaire +4 more sources
Modeling Unknown Class Centers for Metric Learning on Person Re-Identification
Metric learning is one of the major methods for person re-identification. Most existing metric learning methods for person re-identification first generate the pairwise constraints where the sample pairs with the same labels consist of the positive set ...
Yuan Yuan, Jian'an Zhang, Qi Wang
doaj +1 more source
Improving Person Re-Identification with Temporal Constraints [PDF]
In this paper we introduce an image-based person re-identification dataset collected across five non-overlapping camera views in the large and busy airport in Dublin, Ireland. Unlike all publicly available image-based datasets, our dataset contains timestamp information in addition to frame number, and camera and person IDs.
Dietlmeier, Julia+4 more
openaire +3 more sources
A Comparison of Approaches for Person Re-identification
Advanced surveillance applications often require the ability to re-identify an individual. In the typical context of a sensor network, this means to recognize a subject acquired at one location among a feasible set of candidates acquired at another locations and/or over time. Usually this does not necessarily imply to know the identity, and actually it
RICCIO, Daniel+3 more
openaire +6 more sources
Person re-identification in crowd [PDF]
Person re-identification aims to recognize the same person viewed by disjoint cameras at different time instants and locations. In this paper, after an extensive review of state-of-the-art approaches, we propose a re-identification method that takes into account the appearance of people, the spatial location of cameras and potential paths a person can ...
Riccardo Mazzon+2 more
openaire +2 more sources
Human-in-the-Loop Person Re-identification [PDF]
Current person re-identification (re-id) methods assume that (1) pre-labelled training data are available for every camera pair, (2) the gallery size for re-identification is moderate. Both assumptions scale poorly to real-world applications when camera network size increases and gallery size becomes large.
Tao Xiang+3 more
openaire +3 more sources
Two‐way constraint network for RGB‐Infrared person re‐identification
RGB‐Infrared person re‐identification (RGB‐IR Re‐ID) is a task aiming to retrieve and match person images between RGB images and IR images. Since most surveillance cameras capture RGB images during the day and IR images at night, RGB‐IR Re‐ID is helpful ...
Haitang Zeng+3 more
doaj +1 more source
Semantics-Aligned Representation Learning for Person Re-identification
Person re-identification (reID) aims to match person images to retrieve the ones with the same identity. This is a challenging task, as the images to be matched are generally semantically misaligned due to the diversity of human poses and capture ...
Chen, Zhibo+4 more
core +1 more source