Results 31 to 40 of about 10,393 (248)
Salient Object Segmentation Based on Superpixel and Background Connectivity Prior
Salient object segmentation is well known for detecting and segmenting objects using saliency map as input. In this paper, we propose a salient object segmentation method which integrates saliency, superpixel, and background connectivity prior.
Yuzhen Niu, Chaoran Su, Wenzhong Guo
doaj +1 more source
Visual Object Tracking: The Initialisation Problem [PDF]
Model initialisation is an important component of object tracking. Tracking algorithms are generally provided with the first frame of a sequence and a bounding box (BB) indicating the location of the object.
De Ath, George, Everson, Richard
core +2 more sources
COMPARATIVE ANALYSIS OF SUPERPIXEL SEGMENTATION METHODS
Superpixel segmentation showed to be a useful preprocessing step in many computer vision applications. Superpixel’s purpose is to reduce the redundancy in the image and increase efficiency from the point of view of the next processing task. This led to a variety of algorithms to compute superpixel segmentations, each with individual strengths and ...
SumitKaur, Dr. R.K Bansal
openaire +2 more sources
Texture-Aware Superpixel Segmentation [PDF]
Most superpixel algorithms compute a trade-off between spatial and color features at the pixel level. Hence, they may need fine parameter tuning to balance the two measures, and highly fail to group pixels with similar local texture properties. In this paper, we address these issues with a new Texture-Aware SuperPixel (TASP) method.
Giraud, Rémi +3 more
openaire +3 more sources
Early smoke detection of forest fires based on SVM image segmentation
A smoke detection method is proposed in single-frame video sequence images for forest fire detection in large space and complex scenes. A new superpixel merging algorithm is further studied to improve the existing horizon detection algorithm. This method
Ding Xiong, Lu Yan
doaj +1 more source
Improved Fast Generation of Superpixel Algorithms with Deep Network
Superpixels are the result of over-segmentation of the image and provide an intermediate representation of the image data. It plays an important role in the research of computer vision and other fields. However, the existing superpixel algorithms are non-
SHENG Jiachuan, WANG Jiayuan, LI Yuzhi, WANG Jun
doaj +1 more source
Extended set of superpixel features
Superpixel-based image processing and analysis methods usually use a small set of superpixel features. Expanding the description of superpixels can improve the quality of processing algorithms. In the paper, a set of 25 basic superpixel features of shape,
A.A. Egorova, V.V. Sergeyev
doaj +1 more source
Multiscale Superpixel-Based Sparse Representation for Hyperspectral Image Classification †
Recently, superpixel segmentation has been proven to be a powerful tool for hyperspectral image (HSI) classification. Nonetheless, the selection of the optimal superpixel size is a nontrivial task.
Shuzhen Zhang +3 more
doaj +1 more source
Most of the existing superpixel segmentation-based synthetic aperture radar (SAR) target detection algorithms cannot keep the independence of small targets under complex background, especially when the size of the targets varies greatly.
Shichao Chen +5 more
doaj +1 more source
Multiscale Superpixel Segmentation With Deep Features for Change Detection
In this paper, a novel change detection technique is proposed based on multiscale superpixel segmentation and stacked denoising autoencoders (SDAE). This approach is designed to achieve superpixel-based change detection, in which the basic analysis unit ...
Yu Lei +4 more
doaj +1 more source

