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The spatio-temporal data is our cognition to external matter and the spatio-temporal data model is the fundamental basic to manage the spatio-temporal data. The spatio-temporal object is always changi...
Treating visual object tracking as foreground and background classification problem has attracted much attention in the past decade. Most methods adopt mean shift or brute force search to perform obje...
In this paper, we propose a group-sensitive multiple kernel learning (GS-MKL) method to accommodate the intra-class diversity and the inter-class correlation for object categorization. By introducing ...
A new algorithm which associates (Multiple Signal Classification) MUSIC with acoustic scattering model for bearing and range estimation is proposed. This algorithm takes into account the reflection an...
In this paper, we present a multimedia scene representation application implementing MPEG4-Part 20 Lightweight Application Scene Representation standard (LASeR). In an interactive multimedia scene, we...
Image representation has been a key issue in vision research for many years. In order to represent various local image patterns or objects effectively, it is important to study the spatial relationshi...
In this paper, we present a robust and unsupervised approach for recognition of object categories, RTSI-pLSA, which overcomes the weakness of TSI-pLSA in recognizing rotated objects in images. Our app...
Recently the “bag of words” model becomes popular in the approaches to object recognition. These approaches model an image as a collection of local patches called “visual words”, and recognize object...
In this paper, we present a robust and unsupervised approach for recognition of object categories, RTSI-pLSA, which overcomes the weakness of TSI-pLSA in recognizing rotated objects in images. Our app...
In this paper, we propose an object detection approach using spatial histogram features. As spatial histograms consist of marginal distributions of an image over local patches, they can preserve textu...
Abstract—Feature extraction for object representation plays an important role in automatic object detection system. As the spatial histograms consist of marginal distribution of image over local pat...
Moving object segmentation in compressed domain plays an important role in many real-time applications, e.g. video indexing,video transcoding, video surveillance, etc. Because H.264/AVC is the up-to-d...
In this paper, a region-based spatio-temporal Markov random field (STMRF) model is proposed to segment moving objects semantically. The STMRF model combines segmentation results of four successive fr...
This paper presents a novel block-based moving region detection algorithm to segment objects. The frame is first partitioned into homogeneous regions. Moving region is then determined by a voting proc...

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