Action-Driven Visual Object Tracking With Deep Reinforcement Learning
72
Citation
52
Reference
10
Related Paper
Citation Trend
Abstract:
In this paper, we propose an efficient visual tracker, which directly captures a bounding box containing the target object in a video by means of sequential actions learned using deep neural networks. The proposed deep neural network to control tracking actions is pretrained using various training video sequences and fine-tuned during actual tracking for online adaptation to a change of target and background. The pretraining is done by utilizing deep reinforcement learning (RL) as well as supervised learning. The use of RL enables even partially labeled data to be successfully utilized for semisupervised learning. Through the evaluation of the object tracking benchmark data set, the proposed tracker is validated to achieve a competitive performance at three times the speed of existing deep network-based trackers. The fast version of the proposed method, which operates in real time on graphics processing unit, outperforms the state-of-the-art real-time trackers with an accuracy improvement of more than 8%.Keywords:
BitTorrent tracker
Benchmark (surveying)
Minimum bounding box
Tracking (education)
Though not often mentioned, the price point of many eye tracking systems may be a factor limiting their adoption in research. Recently, several inexpensive eye trackers have appeared on the market, but to date little systematic research has been conducted to validate these systems. The present experiment attempted to address this gap by evaluating and comparing five different eye trackers, the Eye Tribe Tracker, Tobii EyeX, Seeing Machines faceLAB, Smart Eye Pro, and Smart Eye Aurora for their gaze tracking accuracy and precision. Results suggest that all evaluated trackers maintained acceptable accuracy and precision, but lower cost systems frequently also experienced high rates of data loss, suggesting that researchers adopting low cost systems such as those evaluated here should be judicious in their research usage.
BitTorrent tracker
Limiting
Tracking (education)
Cite
Citations (75)
Various eye-trackers have recently become commercially available, but studies on more high-spec eye-tracking system have been conducted. Especially, studies have shown that conventional eye-trackers are rather inflexible in layout. The cameras employed in these eye-trackers, as well as the light sources and user's position are fixed, and only a predefined plane can be the target of the eye-tracking. In this study, we propose a new framework that we call a Free-Target Eye-tracking System, which consists of eye-tracking hardware and a hardware layout solver. We developed a prototype of a hardware layout solver and demonstrated its effectiveness.
BitTorrent tracker
Tracking (education)
Tracking system
Solver
Cite
Citations (2)
BitTorrent tracker
Tracking (education)
Cite
Citations (35)
Eye tracking is a compelling tool for revealing people's spatial-temporal distribution of visual attention. But quality eye tracking hardware is expensive and can only be used with one person at a time. Further, webcam eye tracking systems have significant limitations on head movement and lighting conditions that result in significant data loss and inaccuracies. To address these drawbacks, we introduce a new approach that harnesses the crowd to understand allocation of visual attention. In our approach, crowdsourcing participants use mouse clicks to self-report the positions and trajectory for the following valuable eye tracking measures: first gaze, last gaze and all gazes. We validate our crowdsourcing approach with a user study, which demonstrated good accuracy when compared to a real eye tracker. We then deployed our prototype, GazeCrowd, in a crowdsourcing setting, and showed that it accurately generated gaze heatmaps and trajectory maps. Such an approach will allow designers to evaluate and refine their visual design without requiring the use of limited/expensive eye trackers.
Crowdsourcing
BitTorrent tracker
Tracking (education)
Cite
Citations (30)
BitTorrent tracker
Minimum bounding box
Tracking (education)
Bounding overwatch
Cite
Citations (3)
Eye Gaze Tracking is emerging as a popular method to increase the efficiency as well as to increase the accessibility of computing systems. It has been already employed in various applications as well as many researches are going on to incorporate the concept in various other fields. There are various fields where the systems are employed ranging from ease of accessibility of computing systems [1] to performance of computer graphics processing by the method of foveated rendering [2] and as well as digital marketing analysis [3]. The application of eye gaze trackers is still limited due to its lack of availability as well as the cost of the eye gaze trackers which makes them still a scarce resource for majority of the population. This paper proposes an efficient system for Eye Gaze Tracking and draws a sharp contrast between the different open source software available for Eye Gaze Tracking on the market. The study draws the comparison between two of the most popular open source eye gaze tracking software available in the market. ITU Gaze Tracker [4] PyGame based Eye Tracker [5]. The components proposed for the system are easily available in the market.
BitTorrent tracker
Tracking system
Tracking (education)
Cite
Citations (5)
The development of eye tracking-based applications has witnessed a number of advancements over the past few years. As a result, a number of low cost commercial remote vision-based eye trackers started to appear in the market. Consequently, a number of research communities started to explore the feasibility of extending the eye-tracking capabilities beyond single computer screen and utilize it in multi-screen setup. One of the main challenges for the wide adoption of such eye trackers in multi-screen setup, is their limitations when it comes to an intuitive and reliable way for tracking human eye movements across these multiple screens without losing much of the eye tracking data itself. In this work, a novel data-driven approach based on deep recurrent neural networks for a reliable and responsive switching mechanism between low cost multi-screen eye trackers is proposed. Our approach has achieved a competent results in terms of higher accuracy and lower positive rate in detecting accurately the screen the subject is attending to with F1 measure score of 85%.
BitTorrent tracker
Tracking (education)
Cite
Citations (0)
BitTorrent tracker
Tracking (education)
Cite
Citations (34)
BitTorrent tracker
Scope (computer science)
Tracking (education)
Tracking system
Cite
Citations (2)
Commercial eye-gaze trackers have the potential to be an important tool for quantifying the benefits of new visualization techniques. The expense of such trackers has made their use relatively infrequent in visualization studies. As such, it is difficult for researchers to compare multiple devices - obtaining several demonstration models is impractical in cost and time, and quantitative measures from real-world use are not readily available. In this paper, we present a sample protocol to determine the accuracy of a gaze-tacking device.
BitTorrent tracker
Tacking
Sample (material)
Tracking (education)
Cite
Citations (29)