Models for computer vision are commonly defined either wrt low-level concepts such as
pixels that are to be grouped, or wrt high-level concepts such as semantic objects that are to …

Owing to the massive amount of video data being generated as a result of high proliferation
of surveillance cameras, the manpower to monitor such system is relatively expensive …

In order to track all persons in a scene, the tracking-by-detection paradigm has proven to be
a very effective approach. Yet, relying solely on a single detector is also a major limitation …

This paper presents an overview of the state of the art of three different fields with the shared
characteristics of making use of a network of sensors, with the possible application of …

In this paper, a unified three-layer hierarchical approach for solving tracking problems in
multiple non-overlapping cameras is proposed. Given a video and a set of detections …

In this work, we propose an end-to-end constrained clustering scheme to tackle the person
re-identification (re-id) problem. Deep neural networks (DNN) have recently proven to be …

In this paper, a unified three-layer hierarchical approach for solving tracking problem in a
multiple non-overlapping cameras setting is proposed. Given a video and a set of detections …

This paper presents a new approach for the challenging problem of geo-localization using
image matching in a structured database of city-wide reference images with known GPS …

Abnormal water quality will increase the occlusion rate among fish schools, which causes
difficulties in fish detection and tracking. In order to solve this problem, a multiple fish …

Object tracking refers to the relocation of specific objects in consecutive frames of a video
sequence. Presently, this visual task is still considered an open research issue, and the …