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A movie may be represented as a three-dimensional (3-D) signal and as a spatiotemporal spectrum in a 3-D frequency domain. Most spatiotemporal spectra lie on a theoretical motion plane when an object moves at a uniform velocity in a movie. By calculating the slope of this plane, we can estimate the velocity of the moving object. However, the spatiotemporal spectrum of a frequency analysis method such...
A novel system for the recognition of spatiotemporal hand gestures used in sign language is presented. While recognition of valid sign sequences is an important task in the overall goal of machine recognition of sign language, recognition of movement epenthesis is an important step towards continuous recognition of natural sign language. We propose a framework for recognizing valid sign segments and...
In this paper we propose a gesture perception algorithm using compact one-dimensional representation of spatio-temporal motion-field patches. At the learning stage, motion-field patches are randomly extracted and stored as templates. When generating feature vectors for video sequences, we compare stored templates with video, calculate maximum similarities and save those values as elements of feature...
While various techniques of image deformation have been developed and extensively applied in animation and morphing, there are few works to extend these techniques to handle videos, especially real-time warping of a meaningful moving part in the video like human face. An efficient online algorithm is proposed in this paper to implement real-time face warping for video sequence. We employ AdaBoost...
In this paper we address the problem of localisation and recognition of human activities in unsegmented image sequences. The main contribution of the proposed method is the use of an implicit representation of the spatiotemporal shape of the activity which relies on the spatiotemporal localization of characteristic, sparse, dasiavisual wordspsila and dasiavisual verbspsila. Evidence for the spatiotemporal...
In this paper we propose an optical flow estimation method based on compensating method by using spatiotemporal differentiation. Technique using spatiotemporal differentiation is one of optical flow calculation method. This method enables us to calculate velocity distribution rapidly, but the error in the approximation of derivative coefficients increases as the displacement of the moving pattern...
This work presents a novel approach to the extraction of trajectories in video. It has the advantage of simultaneously processing all spatiotemporal information, i.e. all the video frames, and thus overcoming disadvantages of local approaches. A projection of the video frames over time is used to create a frequency modulated signal, which is then processed with the continuous wavelet transform (CWT)...
In this paper, we propose a framework to model video sequences using spatiotemporal description of video shots. Spatiotemporal volumes are extracted thanks to an efficient segmentation algorithm. Video shots are described by building an adjacency graph which models the visual properties of the volumes and the spatiotemporal relationships between them. The cost of extracting visual descriptors for...
In surveillance applications, search space reduction (SSR) is an essential element to efficient algorithms. In this study, spatial and temporal SSRs are integrated for license plate detection in video sequences; the plates could be extracted robustly and extremely fast. Our method started from spatial SSR by a bi-level one-pass plate extraction (BOPE) algorithm developed to extract plates accurately...
In this paper, we present a novel approach for automatically learning a compact and yet discriminative appearance-based human action model. A video sequence is represented by a bag of spatiotemporal features called video-words by quantizing the extracted 3D interest points (cuboids) from the videos. Our proposed approach is able to automatically discover the optimal number of video-word clusters by...
We propose a new statistical generative model for spatiotemporal video segmentation. The objective is to partition a video sequence into homogeneous segments that can be used as "building blocks" for semantic video segmentation. The baseline framework is a Gaussian mixture model (GMM)-based video modeling approach that involves a six-dimensional spatiotemporal feature space. Specifically,...
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