Particle filter framework for salient object detection in videos
Salient object detection in videos is challenging because of the competing motion in the background, resulting from camera tracking an object of interest, or motion of objects in the foreground. The authors present a fast method to detect salient video objects using particle filters, which are guide...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-06-01
|
| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2013.0298 |
| _version_ | 1797684845965475840 |
|---|---|
| author | Karthik Muthuswamy Deepu Rajan |
| author_facet | Karthik Muthuswamy Deepu Rajan |
| author_sort | Karthik Muthuswamy |
| collection | DOAJ |
| description | Salient object detection in videos is challenging because of the competing motion in the background, resulting from camera tracking an object of interest, or motion of objects in the foreground. The authors present a fast method to detect salient video objects using particle filters, which are guided by spatio‐temporal saliency maps and colour feature with the ability to quickly recover from false detections. The proposed method for generating spatial and motion saliency maps is based on comparing local features with dominant features present in the frame. A region is marked salient if there is a large difference between local and dominant features. For spatial saliency, hue and saturation features are used, while for motion saliency, optical flow vectors are used as features. Experimental results on standard datasets for video segmentation and for saliency detection show superior performance over state‐of‐the‐art methods. |
| first_indexed | 2024-03-12T00:35:36Z |
| format | Article |
| id | doaj.art-f278d5f6060348fd96a52dd5cd126ecb |
| institution | Directory Open Access Journal |
| issn | 1751-9632 1751-9640 |
| language | English |
| last_indexed | 2024-03-12T00:35:36Z |
| publishDate | 2015-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Computer Vision |
| spelling | doaj.art-f278d5f6060348fd96a52dd5cd126ecb2023-09-15T09:37:49ZengWileyIET Computer Vision1751-96321751-96402015-06-019342843810.1049/iet-cvi.2013.0298Particle filter framework for salient object detection in videosKarthik Muthuswamy0Deepu Rajan1Centre for Multimedia and Network TechnologySchool of Computer EngineeringNanyang Technological University50 Nanyang Avenue, N4‐02C‐92 639798SingaporeCentre for Multimedia and Network TechnologySchool of Computer EngineeringNanyang Technological University50 Nanyang Avenue, N4‐02C‐92 639798SingaporeSalient object detection in videos is challenging because of the competing motion in the background, resulting from camera tracking an object of interest, or motion of objects in the foreground. The authors present a fast method to detect salient video objects using particle filters, which are guided by spatio‐temporal saliency maps and colour feature with the ability to quickly recover from false detections. The proposed method for generating spatial and motion saliency maps is based on comparing local features with dominant features present in the frame. A region is marked salient if there is a large difference between local and dominant features. For spatial saliency, hue and saturation features are used, while for motion saliency, optical flow vectors are used as features. Experimental results on standard datasets for video segmentation and for saliency detection show superior performance over state‐of‐the‐art methods.https://doi.org/10.1049/iet-cvi.2013.0298particle filter frameworkobject of interestsalient video object detectionspatiotemporal saliency mapscolour featurespatial saliency maps |
| spellingShingle | Karthik Muthuswamy Deepu Rajan Particle filter framework for salient object detection in videos IET Computer Vision particle filter framework object of interest salient video object detection spatiotemporal saliency maps colour feature spatial saliency maps |
| title | Particle filter framework for salient object detection in videos |
| title_full | Particle filter framework for salient object detection in videos |
| title_fullStr | Particle filter framework for salient object detection in videos |
| title_full_unstemmed | Particle filter framework for salient object detection in videos |
| title_short | Particle filter framework for salient object detection in videos |
| title_sort | particle filter framework for salient object detection in videos |
| topic | particle filter framework object of interest salient video object detection spatiotemporal saliency maps colour feature spatial saliency maps |
| url | https://doi.org/10.1049/iet-cvi.2013.0298 |
| work_keys_str_mv | AT karthikmuthuswamy particlefilterframeworkforsalientobjectdetectioninvideos AT deepurajan particlefilterframeworkforsalientobjectdetectioninvideos |