Transferring learning from multi-person tracking to person re-identification
نویسندگان
چکیده
منابع مشابه
Multi-Channel Pyramid Person Matching Network for Person Re-Identification
In this work, we present a Multi-Channel deep convolutional Pyramid Person Matching Network (MC-PPMN) based on the combination of the semantic-components and the colortexture distributions to address the problem of person reidentification. In particular, we learn separate deep representations for semantic-components and color-texture distributions from two person images and then employ pyramid ...
متن کاملDeep-Person: Learning Discriminative Deep Features for Person Re-Identification
Recently, many methods of person re-identification (ReID) rely on part-based feature representation to learn a discriminative pedestrian descriptor. However, the spatial context between these parts is ignored for the independent extractor on each separate part. In this paper, we propose to apply Long Short-Term Memory (LSTM) in an end-to-end way to model the pedestrian, seen as a sequence of bo...
متن کاملView-Adaptive Metric Learning for Multi-view Person Re-identification
Person re-identification is a challenging problem due to drastic variations in viewpoint, illumination and pose. Most previous works on metric learning learn a global distance metric to handle those variations. Different from them, we propose a view-adaptive metric learning (VAML) method, which adopts different metrics adaptively for different image pairs under varying views. Specifically, give...
متن کاملLearning Affine Hull Representations for Multi-Shot Person Re-Identification
We consider the person re-identification problem, assuming the availability of a sequence of images for each person, commonly referred to as video-based or multi-shot reidentification. We approach this problem from the perspective of learning discriminative distance metric functions. While existing distance metric learning methods typically employ the average feature vector as the data exemplar...
متن کاملScience Deep learning for person re - identification
Person re-identification is the task of ranking a gallery of automatically detected images of persons using a set of query images. This is challenging due to the different poses, viewpoints, occlusions, camera configurations, image distortions, lighting conditions, image resolutions and imperfect detections, which all affects a person re-identification system’s performance. Recently deeply lear...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Integrated Computer-Aided Engineering
سال: 2019
ISSN: 1069-2509,1875-8835
DOI: 10.3233/ica-190603