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Proceedings ArticleDOI

A Motion-Sketch Based Video Retrieval Using MST-CSS Representation

TL;DR: This work proposes a framework for a robust Content Based Video Retrieval (CBVR) system with free hand query sketches, using the Multi-Spectro Temporal-Curvature Scale Space (MST-CSS) representation.
Abstract: In this work, we propose a framework for a robust Content Based Video Retrieval (CBVR) system with free hand query sketches, using the Multi-Spectro Temporal-Curvature Scale Space (MST-CSS) representation. Our designed interface allows sketches to be drawn to depict the shape of the object in motion and its trajectory. We obtain the MST-CSS feature representation using these cues and match with a set of MST-CSS features generated offline from the video clips in the database (gallery). Results are displayed in rank ordered similarity. Experimentation with benchmark datasets shows promising results.
Citations
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Proceedings ArticleDOI
01 Sep 2013
TL;DR: The convergence theory of evolved open curves is established, and the CSS shape representation is investigated, for dealing with the endpoint problem of open curves.
Abstract: The problem of extending the curvature scale-space (CSS) technique to represent open curves is addressed. Various approaches for dealing with the endpoint problem of open curves are considered, and one is selected which allows us to handle the evolution of the open curves as a special case of the evolution of closed curves. The convergence theory of evolved open curves is established, and the CSS shape representation is investigated.

9 citations


Additional excerpts

  • ...Index Terms— Scale-space, shape representation, shape analysis, curve evolution, CSS, digital curves...

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Journal ArticleDOI
TL;DR: This paper highlights comprehensive and extensive review of CBVR techniques for detection of region of interest in a given video and the detection rate of ROI is observed competitive and satisfactory.
Abstract: Content Based Video Retrieval (CBVR) System has been investigated over past decade it’s rooted in many applications like developments and technologies. The demand for extraction of high level semantics contents as well as handling of low level contents in video retrieval systems are still in need. Hence it motivates and encourages many researchers to discover their knowledge across CBVR domain and contribute their work to make the system more effective and useful in developing the system application. This paper highlights comprehensive and extensive review of CBVR techniques for detection of region of interest in a given video. The experiment is carried out for the detection of ROI using ACF detector. The detection rate of ROI is observed competitive and satisfactory.

9 citations


Cites methods from "A Motion-Sketch Based Video Retriev..."

  • ...[78] present a methodology for sketch based CBVR system that combines shape and motion trajectory features....

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Proceedings ArticleDOI
07 Mar 2016
TL;DR: This demo shows how the sketch-based video retrieval of the IMOTION system is used in a collection of roughly 30,000 video shots.
Abstract: The IMOTION system is a content-based video search engine that provides fast and intuitive known item search in large video collections. User interaction consists mainly of sketching, which the system recognizes in real-time and makes suggestions based on both visual appearance of the sketch (what does the sketch look like in terms of colors, edge distribution, etc.) and semantic content (what object is the user sketching). The latter is enabled by a predictive sketch-based UI that identifies likely candidates for the sketched object via state-of-the-art sketch recognition techniques and offers on-screen completion suggestions. In this demo, we show how the sketch-based video retrieval of the IMOTION system is used in a collection of roughly 30,000 video shots. The system indexes collection data with over 30 visual features describing color, edge, motion, and semantic information. Resulting feature data is stored in ADAM, an efficient database system optimized for fast retrieval.

8 citations


Cites methods from "A Motion-Sketch Based Video Retriev..."

  • ...Similarly, a SBVR system based on motion sketching[1] can perform retrieval in 1000+ video clips....

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References
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Proceedings ArticleDOI
23 Aug 2004
TL;DR: This paper construct video representations in terms of local space-time features and integrate such representations with SVM classification schemes for recognition and presents the presented results of action recognition.
Abstract: Local space-time features capture local events in video and can be adapted to the size, the frequency and the velocity of moving patterns. In this paper, we demonstrate how such features can be used for recognizing complex motion patterns. We construct video representations in terms of local space-time features and integrate such representations with SVM classification schemes for recognition. For the purpose of evaluation we introduce a new video database containing 2391 sequences of six human actions performed by 25 people in four different scenarios. The presented results of action recognition justify the proposed method and demonstrate its advantage compared to other relative approaches for action recognition.

3,238 citations

Journal ArticleDOI
TL;DR: A probabilistic method, called the Coherent Point Drift (CPD) algorithm, is introduced for both rigid and nonrigid point set registration and a fast algorithm is introduced that reduces the method computation complexity to linear.
Abstract: Point set registration is a key component in many computer vision tasks. The goal of point set registration is to assign correspondences between two sets of points and to recover the transformation that maps one point set to the other. Multiple factors, including an unknown nonrigid spatial transformation, large dimensionality of point set, noise, and outliers, make the point set registration a challenging problem. We introduce a probabilistic method, called the Coherent Point Drift (CPD) algorithm, for both rigid and nonrigid point set registration. We consider the alignment of two point sets as a probability density estimation problem. We fit the Gaussian mixture model (GMM) centroids (representing the first point set) to the data (the second point set) by maximizing the likelihood. We force the GMM centroids to move coherently as a group to preserve the topological structure of the point sets. In the rigid case, we impose the coherence constraint by reparameterization of GMM centroid locations with rigid parameters and derive a closed form solution of the maximization step of the EM algorithm in arbitrary dimensions. In the nonrigid case, we impose the coherence constraint by regularizing the displacement field and using the variational calculus to derive the optimal transformation. We also introduce a fast algorithm that reduces the method computation complexity to linear. We test the CPD algorithm for both rigid and nonrigid transformations in the presence of noise, outliers, and missing points, where CPD shows accurate results and outperforms current state-of-the-art methods.

2,429 citations


"A Motion-Sketch Based Video Retriev..." refers methods in this paper

  • ...During matching process, we first align the query and model MST-CSS surfaces by registering the peaks using the CPD algorithm [5]....

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Proceedings ArticleDOI
17 Oct 2005
TL;DR: The method is fast, does not require video alignment and is applicable in many scenarios where the background is known, and the robustness of the method is demonstrated to partial occlusions, non-rigid deformations, significant changes in scale and viewpoint, high irregularities in the performance of an action and low quality video.
Abstract: Human action in video sequences can be seen as silhouettes of a moving torso and protruding limbs undergoing articulated motion. We regard human actions as three-dimensional shapes induced by the silhouettes in the space-time volume. We adopt a recent approach by Gorelick et al. (2004) for analyzing 2D shapes and generalize it to deal with volumetric space-time action shapes. Our method utilizes properties of the solution to the Poisson equation to extract space-time features such as local space-time saliency, action dynamics, shape structure and orientation. We show that these features are useful for action recognition, detection and clustering. The method is fast, does not require video alignment and is applicable in (but not limited to) many scenarios where the background is known. Moreover, we demonstrate the robustness of our method to partial occlusions, non-rigid deformations, significant changes in scale and viewpoint, high irregularities in the performance of an action and low quality video

2,186 citations

Journal ArticleDOI
TL;DR: The method is fast, does not require video alignment, and is applicable in many scenarios where the background is known, and the robustness of the method is demonstrated to partial occlusions, nonrigid deformations, significant changes in scale and viewpoint, high irregularities in the performance of an action, and low-quality video.
Abstract: Human action in video sequences can be seen as silhouettes of a moving torso and protruding limbs undergoing articulated motion. We regard human actions as three-dimensional shapes induced by the silhouettes in the space-time volume. We adopt a recent approach [14] for analyzing 2D shapes and generalize it to deal with volumetric space-time action shapes. Our method utilizes properties of the solution to the Poisson equation to extract space-time features such as local space-time saliency, action dynamics, shape structure, and orientation. We show that these features are useful for action recognition, detection, and clustering. The method is fast, does not require video alignment, and is applicable in (but not limited to) many scenarios where the background is known. Moreover, we demonstrate the robustness of our method to partial occlusions, nonrigid deformations, significant changes in scale and viewpoint, high irregularities in the performance of an action, and low-quality video.

1,842 citations


"A Motion-Sketch Based Video Retriev..." refers methods in this paper

  • ...EXPERIMENTS AND RESULTS We have built our own video database consists of (i) realworld video shots obtained at different outdoor locations, using a still (hand-held) Sony camcorder and (ii) subset of publicly available datasets [6] [7]....

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Journal ArticleDOI
TL;DR: A hybrid motion-based video retrieval system to retrieve desired videos from video databases through trajectory matching with the help of the syntactic distance, many impossible candidates can be filtered out in advance and thus the accuracy of video retrieval can be much enhanced.
Abstract: This paper proposes a hybrid motion-based video retrieval system to retrieve desired videos from video databases through trajectory matching. The hybrid method includes a sketch-based scheme and a string-based one to analyze and index a trajectory with more syntactic meanings. First of all, this method uses a sampling technique to extract a set of control points from each trajectory as features. Then, the sketch-based method uses a curve fitting technique to interpolate some missed data in this set of control points. Then, the visual distance between any two trajectories can be directly measured by comparing their position data. The visual distance is good in solving the problem of translation-invariant trajectory matching but poor in solving the problem of partial trajectory matching. Therefore, in addition to the visual distance, the hybrid method uses the string-based scheme to compare any two trajectories according to their syntactic meanings. With the help of the syntactic distance, many impossible candidates can be filtered out in advance and thus the accuracy of video retrieval can be much enhanced. In addition, the problem of partial trajectory matching will become easy to be solved. Thus, even though a partial trajectory is queried, all desired video clips still can be very accurately retrieved. Experimental results have proved the superiority of our proposed method.

89 citations


"A Motion-Sketch Based Video Retriev..." refers background in this paper

  • ...In recent times, researchers have proposed QBVS system based on color and motion descriptors [1] [2], trajectory matching [3] etc....

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