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Tool for Semiautomatic Labeling of Moving Objects in Video Sequences: TSLAB.

Cuevas C, Yáñez EM, García N - Sensors (Basel) (2015)

Bottom Line: An advanced and user-friendly tool for fast labeling of moving objects captured with surveillance sensors is proposed, which is available to the public.The labeling can be performed easily and quickly thanks to a very friendly graphical user interface that allows one to automatize many common operations.This interface also includes some semiautomatic advanced tools that simplify the labeling tasks and drastically reduce the time required to obtain high-quality results.

View Article: PubMed Central - PubMed

Affiliation: Grupo de Tratamiento de Imágenes, Universidad Politécnica de Madrid (UPM), E-28040 Madrid, Spain. ccr@gti.ssr.upm.es.

ABSTRACT
An advanced and user-friendly tool for fast labeling of moving objects captured with surveillance sensors is proposed, which is available to the public. This tool allows the creation of three kinds of labels: moving objects, shadows and occlusions. These labels are created at both the pixel level and object level, which makes them suitable to assess the quality of both moving object detection strategies and tracking algorithms. The labeling can be performed easily and quickly thanks to a very friendly graphical user interface that allows one to automatize many common operations. This interface also includes some semiautomatic advanced tools that simplify the labeling tasks and drastically reduce the time required to obtain high-quality results.

No MeSH data available.


Related in: MedlinePlus

(a) Two original images; (b) masks of layers. Color notation: visible moving objects (VMO) (red), shadows from moving objects (SMO) (green) and occluded moving objects (OMO) (blue).
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f2-sensors-15-15159: (a) Two original images; (b) masks of layers. Color notation: visible moving objects (VMO) (red), shadows from moving objects (SMO) (green) and occluded moving objects (OMO) (blue).

Mentions: Figure 2 shows two original images and their corresponding ground-truth masks, which contain the above-described layers. It can be observed that the top mask presents a VMO layer and a SMO layer, while the bottom mask contains a VMO layer and and OMO layer.


Tool for Semiautomatic Labeling of Moving Objects in Video Sequences: TSLAB.

Cuevas C, Yáñez EM, García N - Sensors (Basel) (2015)

(a) Two original images; (b) masks of layers. Color notation: visible moving objects (VMO) (red), shadows from moving objects (SMO) (green) and occluded moving objects (OMO) (blue).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541825&req=5

f2-sensors-15-15159: (a) Two original images; (b) masks of layers. Color notation: visible moving objects (VMO) (red), shadows from moving objects (SMO) (green) and occluded moving objects (OMO) (blue).
Mentions: Figure 2 shows two original images and their corresponding ground-truth masks, which contain the above-described layers. It can be observed that the top mask presents a VMO layer and a SMO layer, while the bottom mask contains a VMO layer and and OMO layer.

Bottom Line: An advanced and user-friendly tool for fast labeling of moving objects captured with surveillance sensors is proposed, which is available to the public.The labeling can be performed easily and quickly thanks to a very friendly graphical user interface that allows one to automatize many common operations.This interface also includes some semiautomatic advanced tools that simplify the labeling tasks and drastically reduce the time required to obtain high-quality results.

View Article: PubMed Central - PubMed

Affiliation: Grupo de Tratamiento de Imágenes, Universidad Politécnica de Madrid (UPM), E-28040 Madrid, Spain. ccr@gti.ssr.upm.es.

ABSTRACT
An advanced and user-friendly tool for fast labeling of moving objects captured with surveillance sensors is proposed, which is available to the public. This tool allows the creation of three kinds of labels: moving objects, shadows and occlusions. These labels are created at both the pixel level and object level, which makes them suitable to assess the quality of both moving object detection strategies and tracking algorithms. The labeling can be performed easily and quickly thanks to a very friendly graphical user interface that allows one to automatize many common operations. This interface also includes some semiautomatic advanced tools that simplify the labeling tasks and drastically reduce the time required to obtain high-quality results.

No MeSH data available.


Related in: MedlinePlus