2009 XXII Brazilian Symposium on Computer Graphics and Image Processing 2009
DOI: 10.1109/sibgrapi.2009.17
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Spatio-Temporal Frames in a Bag-of-Visual-Features Approach for Human Actions Recognition

Abstract: Abstract-The recognition of human actions from videos has several interesting and important applications, and a vast amount of different approaches has been proposed for this task in different settings. Such approaches can be broadly categorized in model-based and model-free. Typically, model-based approaches work only in very constrained settings, and because of that, a number of model-free approaches appeared in the last years. Among them, those based in bag-of-visual-features (BoVF) have been proving to be … Show more

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Cited by 9 publications
(5 citation statements)
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“…The use of space-time features is presented in the work [7]. The Bag of Visual Features (BoVF) method is used, which consists of the following steps: characteristic points detection and description (SIFT algorithm), creating a dictionary of the extracted features (using clustering), assigning each detected point to a word from the dictionary (using the smallest distance criterion) and creating a histogram of used "visual words".…”
Section: Human Action Recognition Approaches Reviewmentioning
confidence: 99%
“…The use of space-time features is presented in the work [7]. The Bag of Visual Features (BoVF) method is used, which consists of the following steps: characteristic points detection and description (SIFT algorithm), creating a dictionary of the extracted features (using clustering), assigning each detected point to a word from the dictionary (using the smallest distance criterion) and creating a histogram of used "visual words".…”
Section: Human Action Recognition Approaches Reviewmentioning
confidence: 99%
“…A pixel Gi(t) at level Gi maps to a pixel G0(2 i t). For example, G1(3) mapped to G0 (6) and G2(1) mapped to G0(4).…”
Section: Spatio-temporal Difference Of Gaussian Pyramidmentioning
confidence: 99%
“…The assumption here is that spatio-temporal events can be described by common interest points between the spatial axis (appearance information) and the temporal axis (motion information). Lopes et al presented an approach to forming a spatio-temporal volume by stacking a set of frames from a video signal [6]. There are three directions to slice this volume into planes, as illustrated in Figure 3.…”
Section: Interest Points Detectionmentioning
confidence: 99%
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“…However, there are still some unsolved issues such as background clutter, viewpoint variation, illumination change and class variability [2]. Recently, significant progress has been demonstrated with spatio-temporal feature representation along with variations of the most popular and widely used bag of visual words approaches (BoVW) [3], which have the ability to handle viewpoint independence, occlusion and scale invariance [4,5]. Therefore, there has been a growing interest in exploring the potential of possible variants of the classical BoVW approach, which characterizes actions using a histogram of feature occurrence after clustering [6].…”
Section: Introductionmentioning
confidence: 99%