Deep Directional Network for Object Tracking
نویسندگان
چکیده
منابع مشابه
Convolutional Gating Network for Object Tracking
Object tracking through multiple cameras is a popular research topic in security and surveillance systems especially when human objects are the target. However, occlusion is one of the challenging problems for the tracking process. This paper proposes a multiple-camera-based cooperative tracking method to overcome the occlusion problem. The paper presents a new model for combining convolutiona...
متن کاملDeep Network Flow for Multi-Object Tracking: Supplemental Material
The supplemental material of our deep network flow approach for multi-object tracking contains the following items: • Details on the formulation of deep network flows (Section 1) • An on-line version of the tracker (Section 2) • Qualitative results (Section 3) 1. Details on the formulation of deep network flows First, we want to provide further details of our formulation of deep network flows a...
متن کاملVisual Tracking Utilizing Object Concept from Deep Learning Network
Despite having achieved good performance, visual tracking is still an open area of research, especially when target undergoes serious appearance changes which are not included in the model. So, in this paper, we replace the appearance model by a concept model which is learned from large-scale datasets using a deep learning network. The concept model is a combination of high-level semantic infor...
متن کاملDeep-LK for Efficient Adaptive Object Tracking
In this paper we present a new approach for efficient regression based object tracking which we refer to as DeepLK. Our approach is closely related to the Generic Object Tracking Using Regression Networks (GOTURN) framework of Held et al. [16]. We make the following contributions. First, we demonstrate that there is a theoretical relationship between siamese regression networks like GOTURN and ...
متن کاملDeep Deformation Network for Object Landmark Localization
We propose a novel cascaded framework, namely deep deformation network (DDN), for localizing landmarks in non-rigid objects. The hallmarks of DDN are its incorporation of geometric constraints within a convolutional neural network (CNN) framework, ease and efficiency of training, as well as generality of application. A novel shape basis network (SBN) forms the first stage of the cascade, whereb...
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: Algorithms
سال: 2018
ISSN: 1999-4893
DOI: 10.3390/a11110178