Simulation Videos for Understanding Occlusion Effects on Kernel Based Object Tracking

Lee, Beng Yong; Liew, Lee Hung; Cheah, Wai Shiang; Wang, Yin Chai

doi:10.1007/978-94-007-5699-1_15

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…in their occlusion scenarios and the attempts to simplify such videos (e.g., [78]) are very premature.…”

Section: Occlusion Scenariosmentioning

confidence: 99%

“…It is clear that such datasets are not specifically focused on occlusion, with few videos including only [78] 64 Simulated occlusion videos, 2012 TB-50 [7] Popular videos benchmark, 2013 Princeton RGBD [72] Kinect video with occlusions, 2013 a subset of possible occlusions. So far, valuable attempts have been made to alleviate this shortcomings such as [78] which created 64 simulation video sequences to experiment the effectiveness of each tracking method in various occlusion scenarios. The authors of this study tried to isolate other tracking challenges such as shadow, illumination changes and moving background from the occlusion scenarios.…”

Section: Datasetsmentioning

confidence: 99%

“…Several attempts have been made to describe the occlusion space, but only scratched its surface. Lee et al [78] simulates 64 occlusion scenarios using different motion patterns (8 uniform trajectory and 8 nonuniform trajectory) and occlusion types (no occlusion, partial occlusion, full occlusion, long occlusion). In their experiment they used two rigid convex objects so that many complexities of dealing with non-rigid objects are relaxed.…”

Section: Occlusion Scenariosmentioning

confidence: 99%

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The State-of-the-Art in Handling Occlusions for Visual Object Tracking

Meshgi

Ishii

2015

IEICE Trans. Inf. & Syst.

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SUMMARYThis paper reports on the trending literature of occlusion handling in the task of online visual tracking. The discussion first explores visual tracking realm and pinpoints the necessity of dedicated attention to the occlusion problem. The findings suggest that although occlusion detection facilitated tracking impressively, it has been largely ignored. The literature further showed that the mainstream of the research is gathered around human tracking and crowd analysis. This is followed by a novel taxonomy of types of occlusion and challenges arising from it, during and after the emergence of an occlusion. The discussion then focuses on an investigation of the approaches to handle the occlusion in the frame-by-frame basis. Literature analysis reveals that researchers examined every aspect of a tracker design that is hypothesized as beneficial in the robust tracking under occlusion. State-of-the-art solutions identified in the literature involved various camera settings, simplifying assumptions, appearance and motion models, target state representations and observation models. The identified clusters are then analyzed and discussed, and their merits and demerits are explained. Finally, areas of potential for future research are presented.

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“…in their occlusion scenarios and the attempts to simplify such videos (e.g., [78]) are very premature.…”

Section: Occlusion Scenariosmentioning

confidence: 99%

Section: Datasetsmentioning

confidence: 99%

Section: Occlusion Scenariosmentioning

confidence: 99%

See 1 more Smart Citation

The State-of-the-Art in Handling Occlusions for Visual Object Tracking

Meshgi

Ishii

2015

IEICE Trans. Inf. & Syst.

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Synthetic Data for Deep Learning

Nikolenko

2021

Springer Optimization and Its Applications

153

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Aims and ScopeOptimization has continued to expand in all directions at an astonishing rate. New algorithmic and theoretical techniques are continually developing and the diffusion into other disciplines is proceeding at a rapid pace, with a spot light on machine learning, artificial intelligence, and quantum computing. Our knowledge of all aspects of the field has grown even more profound. At the same time, one of the most striking trends in optimization is the constantly increasing emphasis on the interdisciplinary nature of the field. Optimization has been a basic tool in areas not limited to applied mathematics, engineering, medicine, economics, computer science, operations research, and other sciences.The series Springer Optimization and Its Applications (SOIA) aims to publish state-of-the-art expository works (monographs, contributed volumes, textbooks, handbooks) that focus on theory, methods, and applications of optimization. Topics covered include, but are not limited to, nonlinear optimization, combinatorial optimization, continuous optimization, stochastic optimization, Bayesian optimization, optimal control, discrete optimization, multi-objective optimization, and more. New to the series portfolio include Works at the intersection of optimization and machine learning, artificial intelligence, and quantum computing.Volumes from this series are indexed by Web of Science, zbMATH, Mathematical Reviews, and SCOPUS.

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