• Title/Summary/Keyword: Primitive Motion

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Anomalous Event Detection in Traffic Video Based on Sequential Temporal Patterns of Spatial Interval Events

  • Ashok Kumar, P.M.;Vaidehi, V.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.1
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    • pp.169-189
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    • 2015
  • Detection of anomalous events from video streams is a challenging problem in many video surveillance applications. One such application that has received significant attention from the computer vision community is traffic video surveillance. In this paper, a Lossy Count based Sequential Temporal Pattern mining approach (LC-STP) is proposed for detecting spatio-temporal abnormal events (such as a traffic violation at junction) from sequences of video streams. The proposed approach relies mainly on spatial abstractions of each object, mining frequent temporal patterns in a sequence of video frames to form a regular temporal pattern. In order to detect each object in every frame, the input video is first pre-processed by applying Gaussian Mixture Models. After the detection of foreground objects, the tracking is carried out using block motion estimation by the three-step search method. The primitive events of the object are represented by assigning spatial and temporal symbols corresponding to their location and time information. These primitive events are analyzed to form a temporal pattern in a sequence of video frames, representing temporal relation between various object's primitive events. This is repeated for each window of sequences, and the support for temporal sequence is obtained based on LC-STP to discover regular patterns of normal events. Events deviating from these patterns are identified as anomalies. Unlike the traditional frequent item set mining methods, the proposed method generates maximal frequent patterns without candidate generation. Furthermore, experimental results show that the proposed method performs well and can detect video anomalies in real traffic video data.

A study on the motion decision of the arm using pattern recognition of EMG signal (EMG신호의 패턴인식을 이용한 동작판정에 관한 연구)

  • 홍석교;고영길;유근호
    • 제어로봇시스템학회:학술대회논문집
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    • 1987.10b
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    • pp.694-698
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    • 1987
  • In this paper, the primitive and double combined motion classification of the arm is discussed using pattern recognition of EM signal. The EM signals are detected from Ag-Ag/Cl surface electrodes, and IBM PC, calculated the Likelyhood probability and the decision function on the feature space of integral absolute value. Multiclass decision rule is introduced for higher decision rate. On our experimental results from expert simulator, the decision rate of more than 78% can be obtained.

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Qualitative Representation of Spatial Configuration of Mechanisms and Spatial Behavior Reasoning Using Sign Algebra (메커니즘 공간 배치의 정성적 표현과 부호 대수를 이용한 공간 거동 추론)

  • 한영현;이건우
    • Korean Journal of Computational Design and Engineering
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    • v.5 no.4
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    • pp.380-392
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    • 2000
  • This paper proposes a qualitative reasoning approach for the spatial configuration of mechanisms that could be applied in the early phase of the conceptual design. The spatial configuration problem addressed in this paper involves the relative direction and position between the input and output motion, and the orientation of the constituent primitive mechanisms of a mechanism. The knowledge of spatial configuration of a primitive mechanism is represented in a matrix form called spatial configuration matrix. This matrix provides a compact and convenient representation scheme for the spatial knowledge, and facilitates the manipulation of the relevant spatial knowledge. Using this spatial knowledge of the constituent primitive mechanisms, the overall configuration of a mechanism is described and identified by a spatial configuration state matrix. This matrix is obtained by using a qualitative reasoning method based on sign algebra and is used to represent the qualitative behavior of the mechanism. The matrix-based representation scheme allows handling the involved spatial knowledge simultaneously and the proposed reasoning method enables the designer to predict the spatial behavior of a mechanism without knowing specific dimension of the components of the mechanism.

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Argument Linking in Korean Motion Verb Constructions with Special Attention to Measuring Out (움직임 동사와 논항 연결, 재어나누기)

  • Yang, Jeong-Seok
    • Language and Information
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    • v.3 no.1
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    • pp.39-63
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    • 1999
  • Korean manner-of-motion verbs have different characteristics from locomotion verbs syntactically and semantically, and they are aptly encoded as having the primitive semantic element MOVE, not GO of Jackendoff(1990)'s Conceptual Semantics framework. This point is shown on the basis of their behavior, the inability to take the Goal 'NP-lo' phrases, the Purposive 'S-le' clauses, the 'NP-ey' phrases, and the atelic interpretation. It is further shown that the apparent locomotion verb behavior of some manner-of-motion verbs, 'exocentric' phenomenon in their meaning composition, is merely a transferred aspect of manner-of-motion verbs. Three kinds of strategies, transformational, quasi-transformational, and lexical ones, are examined to describe this phenomenon, and the lexical one is determined to be the most appropriate. The remaining part of this paper pursues the possibility of adopting Tenny's(1987, 1994) 'Aspectual Interface Hypothesis' in establishing an argument linking system with special attention to 'measuring-out', but concludes that the hypothesis can be accepted only in a restricted part of verbs, and with a modified notion of measuring-out like Jackendoff's(1996).

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Behavior Planning for Humanoid Robot Using Behavior Primitive (행동 프리미티브 기반 휴머노이드 로봇의 행동 계획)

  • Noh, Su-Hee;Kim, Yong-Tae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.1
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    • pp.108-114
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    • 2009
  • In this paper, we presents a behavior planning for humanoid robots using behavior primitive in 3 dimensional workspace. Also, we define behavior primitives that humanoid robot accomplishes various tasks effectively. Humanoid robot obtains information of the outside environment and its inner information from various sensors in complex workspace with various obstacles. We verify our approach on a developed small humanoid robot using embedded vision and sensor system in a experimental environment. The experimental results show that the humanoid robot performs its tasks fast and effectively.

Motion Planning for Legged Robots Using Locomotion Primitives in the 3D Workspace (3차원 작업공간에서 보행 프리미티브를 이용한 다리형 로봇의 운동 계획)

  • Kim, Yong-Tae;Kim, Han-Jung
    • The Journal of Korea Robotics Society
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    • v.2 no.3
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    • pp.275-281
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    • 2007
  • This paper presents a motion planning strategy for legged robots using locomotion primitives in the complex 3D environments. First, we define configuration, motion primitives and locomotion primitives for legged robots. A hierarchical motion planning method based on a combination of 2.5 dimensional maps of the 3D workspace is proposed. A global navigation map is obtained using 2.5 dimensional maps such as an obstacle height map, a passage map, and a gradient map of obstacles to distinguish obstacles. A high-level path planner finds a global path from a 2D navigation map. A mid-level planner creates sub-goals that help the legged robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. A local obstacle map that describes the edge or border of the obstacles is used to find the sub-goals along the global path. A low-level planner searches for a feasible sequence of locomotion primitives between sub-goals. We use heuristic algorithm in local motion planner. The proposed planning method is verified by both locomotion and soccer experiments on a small biped robot in a cluttered environment. Experiment results show an improvement in motion stability.

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Generation Method of Robot Movement Using Evolutionary Algorithm (진화 알고리즘을 사용한 휴머노이드 로봇의 동작 학습 알고리즘)

  • Park, Ga-Lam;Ra, Syung-Kwon;Kim, Chan-Hwan;Song, Jae-Bok
    • Proceedings of the KIEE Conference
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    • 2007.10a
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    • pp.315-316
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    • 2007
  • This paper presents a new methodology to improve movement database for a humanoid robot. The database is initially full of human motions so that the kinetics characteristics of human movement are immanent in it. then, the database is updated to the pseudo-optimal motions for the humanoid robot to perform more natural motions, which contain the kinetics characteristics of robot. for this, we use the evolutionary algorithm. the methodology consists of two processes : (1) the offline imitation learning of human movement and (2) the online generation of natural motion. The offline process improve the initial human motion database using the evolutionary algorithm and inverse dynamics-based optimization. The optimization procedure generate new motions using the movement primitive database, minimizing the joint torque. This learning process produces a new database that can endow the humanoid robot with natural motions, which requires minimal torques. In online process, using the linear combination of the motion primitive in this updated database, the humanoid robot can generate the natural motions in real time. The proposed framework gives a systematic methodology for a humanoid robot to learn natural motions from human motions considering dynamics of the robot. The experiment of catching a ball thrown by a man is performed to show the feasibility of the proposed framework.

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Microprocessor Control of a Prosthetic Arm by EMG Pattern Recognition (EMG 패턴인식을 이용한 인공팔의 마이크로프로세서 제어)

  • Hong, Suk-Kyo
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.33 no.10
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    • pp.381-386
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    • 1984
  • This paper deals with the microcomputer realization of EMG pattern recognition system which provides identification of motion commands from the EMG signals for the on-line control of a prosthetic arm. A probabilistic model of pattern is formulated in the feature space of integral absolute value(IAV) to describe the relation between a motion command and the location of corresponding pattern. This model enables the derivation of sample density function of a command in the feature space of IAV. Classification is caried out through the multiclass sequential decision process, where the decision rule and the stopping rule of the process are designed by using the simple mathematical formulas defined as the likelihood probability and the decision measure, respectively. Some floating point algorithms such as addition, multiplication, division, square root and exponential function are developed for calculating the probability density functions and the decision measure. Only six primitive motions and one no motion are incorporated in this paper.

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An Application of Screw Motions for Mechanical Assemblies (기계부품들의 조립 및 해체과정 설계를 위한 스크류이론의 응용)

  • 김재정
    • Korean Journal of Computational Design and Engineering
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    • v.2 no.1
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    • pp.60-67
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    • 1997
  • CAD systems offer a variety of techniques for designing and rendering models of static 3D objects and even of mechanisms, but relatively few tools exist for interactively specifying arbitrary movements of rigid bodies through space. Such tools are essential, not only for artistic animation, but also, for planning and demonstrating assembly and disassembly procedure of manufactured products. A rigid body motion is a continuous mapping from the time domain to a set of positions. To relieve the designers from the burden of specifying this mapping in abstract mathematical terms, combinations of simple rigid motion primitives, such as linear translations or constant axis rotations, are often used. These simple motions are planar and thus ill-suited for approximating arbitrary motions in 3D-space. Instead, we propose the screw motion primitive, a special combination of linear translations and constant axis rotations, which has a simple geometric representation that can be automatically and unambiguously computed from the starting and ending positions of the moving body. Although, any two positions may be interpolated by an infinity of motions, we chose the screw motion for its relative generality and its computational advantages. The paper covers original algorithms for computing the screw motions from interpolated positions and envelopes of swept regions to predict collisions.

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On the Circulation in the Jinhae Bay using the Princeton Ocean Model -I. Characteristic in Vertical Tidal Motion-

  • Hong Chul-hoon
    • Fisheries and Aquatic Sciences
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    • v.1 no.2
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    • pp.168-179
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    • 1998
  • Circulation in the Jinhae Bay in the southern sea of Korea is examined using the Princeton Ocean Model (POM) with a free surface in a sigma coordinate, governed by primitive equations. The model well corresponds to the time series of the observed velocities at several layers obtained from a long-term mooring observation. In the residual velocity field of the model, persistent downward flow fields are formed along the central deep regions in the bay, and they are caused by bottom topographic effect. In addition, a comparison between a depth-averaged (2D) model and the POM is given, and a dependance of the results on bottom drag coefficient is also examined.

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