Recently, tracking-by-detection has become a popular paradigm in Multiple-object tracking (MOT) for its concise pipeline. Many current works first associate the detections to form track proposals and then score proposalns by manual functions select best. However, long-term information is lost this way due detection failure or heavy occlusion. In paper, Extendable Multiple Nodes Tracking framework (EMNT) introduced model association. Instead of detections, EMNT creates four basic types nodes...

Recently, most multiple object tracking (MOT) algorithms adopt the idea of tracking-by-detection. Relevant research shows that performance detector obviously affects tracker, while improvement is gradually slowing down in recent years. Therefore, trackers using tracklet (short trajectory) are proposed to generate more complete trajectories. Although there various generation algorithms, fragmentation problem still often occurs crowded scenes. In this paper, we introduce an iterative...

In recent years, the demand for intelligent devices related to Internet of Things (IoT) is rapidly increasing. field computer vision, many algorithms have been preinstalled in IoT achieve higher efficiency, such as face recognition, area detection, target tracking, etc. Tracking an important but complex task that needs high efficiency solutions real applications. There a common assumption detection can only represent one pedestrian describe nonoverlapping physical space. fact, pixels image...

Recent progress in multi-object tracking (MOT) has shown great significance of a robust scoring mechanism for potential tracks. However, the lack available data MOT makes it difficult to learn general mechanism. Multiple cues including appearance, motion and etc., are limitedly utilized current manual functions. In this paper, we propose Nodes Tracking (MNT) framework that adapts most trackers. Based on framework, Recurrent Unit (RTU) is designed score tracks through long-term information....

For an intelligent transportation system, multiple object tracking (MOT) is more challenging from the traditional static surveillance camera to mobile devices of Internet Things (IoT). To cope with this problem, previous works always rely on additional information multivision, various sensors, or precalibration. Only based a monocular camera, we propose hybrid motion model improve accuracy in devices. First, evaluates hypotheses by measuring optical flow similarity and transition smoothness...

Data association is one of the key research in tracking-by-detection framework. Due to frequent interactions among targets, there are various relationships trajectories crowded scenes which leads problems data association, such as ambiguity, omission, etc. To handle these problems, we propose hypothesis-testing based tracking (HTBT) framework build potential associations between target by constructing and testing hypotheses. In addition, a spatio-temporal interaction graph (STIG) model...

Multi-object tracking (MOT) has become a hot task in multi-media analysis. It not only locates the objects but also maintains their unique identities. However, previous methods encounter failures complex scenes, since they lose most of attributes each target. In this paper, we formulate MOT problem as Tracking Game and propose Self-adaptative Agent Tracker (SAT) framework to solve problem. The roles are divided into two classes including agent player game organizer. organizer controls...

Remarkable progress has been made in the field of multi-object tracking. Although tracking-by-detection recently became one most popular frameworks, it still main drawback: this approach relies heavily on quality detection. Thus, missing detections caused by partial occlusion usually lead to fragment problem. To address problem, paper introduces supervoxels represent objects with occlusion, even for detections. We first extract superpixels foreground, and then our proposed supervoxel...

Abstract Person image generation aims to synthesize realistic person images that follow the same distribution as given dataset. Previous attempts can be generally categorized into two classes: conditional GAN and unconditional GAN. The former usually uses pose information condition make transfer using generated have identity source person. latter generates from scratch, real are only used references for discriminator. While is widely studied, also worth exploring because it with new...

We carry out teaching based on optoelectronic related course group, aiming at junior students majored in Optoelectronic Information Science and Engineering. " System Course Project is product-designing-oriented lasts for a whole semester. It provides chance to experience the process of product designing, improve their abilities search literature, proof schemes, design implement schemes. In process, each project topic carefully selected repeatedly refined guarantee projects with knowledge...

The person re-identification (re-ID) problem has attracted growing interest in the computer vision community. Most public re-ID datasets are captured by multiple non-overlapping cameras, and same may appear dissimilar different camera views due to variances of illuminations, viewpoints postures. These differences, collectively referred as style variance, make still a challenging problem. Recently, researchers have attempted solve this using generative models. adversarial network (GAN) is...

Multi-object trackers make the association almost perfectly when no occlusion occurred between two or more targets. However, it is hard to extract reliable features on account of partial caused by a nearby object, which often leads tracking failure. In this paper, we utilize mask guide attention neural network in order focus visible part target and design tracklet-level feature extraction method. Then, framework proposed based guided fusion multi-hypothesis algorithm. Comprehensive...

This paper presents a theoretical model of frequency feedback control loops for tunable transmitter stabilization. The simulation results can provide guidance the design stabilization circuits transmitters in future OPS/OBS networks.