• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2191-2203
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• 2011

In this paper, we propose a fast and robust algorithm for fighting behavior detection based on Motion Vectors (MV), in order to solve the problem of low speed and weak robustness in traditional fighting behavior detection. Firstly, we analyze the characteristics of fighting scenes and activities, and then use motion estimation algorithm based on block-matching to calculate MV of motion regions. Secondly, we extract features from magnitudes and directions of MV, and normalize these features by using Joint Gaussian Membership Function, and then fuse these features by using weighted arithmetic average method. Finally, we present the conception of Average Maximum Violence Index (AMVI) to judge the fighting behavior in surveillance scenes. Experiments show that the new algorithm achieves high speed and strong robustness for fighting behavior detection in surveillance scenes.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1189-1199
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• 2003

This paper presents a new method for the motion detection of vehicles using hierarchical motion estimation and parallel processing. It captures the road image by using a CMOS sensor. It divides the captured image into small blocks and detects the motion of each block by using a block-matching method which is based on a hierarchical motion estimation and parallel processing for the real-time processing. The parallelism is achieved by using tile pipeline and the data flow technique. The proposed method has been implemented by using an embedded system. The proposed block matching algorithm has been implemented on PLDs(Programmable Logic Device) and clustering algorithm has been implemented by ARM processor. Experimental results show that the proposed system detects the motion of vehicles in real-time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.4
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• pp.779-785
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• 2007

Moving object detection is very important for video surveillance in modern days. In special case, we can categorize motions into two types-salient and non-salient motion. In this paper, we first calculate temporal difference image for extract moving objects and adapt to dynamic environments and next, we also propose a new algorithm to detect salient motion information in complex environment by combining temporal difference image and binary block image which is calculated by motion vector using the newest MPEG-4 and EPZS, and it is very effective to detect objects in a complex environment that many various motions are mixed.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2008.04a
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• pp.135-138
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• 2008

Many Victims and property damage are caused in fires. In this paper, an flame detection algorithm is proposed to early alarm fires. The proposed flame detection algorithm is based on 2-stage decision strategy of video processing. The first decision is to check with color distribution of input vidoe. In the second, the candidated region is settled as fire region with activity. As a result of simulation, it is shown that the proposed algorithm is useful for fire recognition.

• Journal of Sensor Science and Technology
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• v.13 no.3
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• pp.188-194
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• 2004

With a remarkable advance in CMOS (complimentary metal-oxide-semiconductor) process technology, a variety of vision sensors with signal processing circuits for complicated functions are actively being developed. Especially, as the principles of signal processing in human retina have been revealed, a series of vision chips imitating human retina have been reported. Human retina is able to detect the edge and motion of an object effectively. The edge detection among the several functions of the retina is accomplished by the cells called photoreceptor, horizontal cell and bipolar cell. We designed a CMOS vision chip by modeling cells of the retina as hardwares involved in edge and motion detection. The designed vision chip was fabricated using $0.6{\mu}m$ CMOS process and the characteristics were measured. Having reliable output characteristics, this chip can be used at the input stage for many applications, like targe tracking system, fingerprint recognition system, human-friendly robot system and etc.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.1
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• pp.44-52
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• 2008

In this paper we consider detecting collisions between characters whose motion is specified by motion capture data. Since we are targeting on massive crowd simulation, we only consider rough collisions, modeling the characters as a disk in the floor plane. To provide efficient collision detection, we introduce a hierarchical bounding volume, the Motion Oriented Bounding Box tree (MOBB tree). A MOBBtree stores space-time bounds of a motion clip. In crowd animation tests, MOBB trees performance improvements ranging between two and an order of magnitude.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.21-24
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• 2002

This paper presents a new method for the motion detection of vehicles using hierarchical motion estimation and parallel processing. It captures the road image by using a CMOS sensor. It divides the captured image into small blocks and detects the motion of each block by using a block-matching method which is based on a hierarchical motion estimation and parallel processing for the real-time processing. The parallelism is achieved by using the pipeline and the data flow technique. The proposed method has been implemented with an embedded system. Experimental results show that the proposed method detects the motion of vehicles in real-time.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2237-2239
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• 1998

A limitation is assumed that In this paper, a generalized method is proposed to extract a period of a motion of on object. To detect a periodic motion, we put restrictions on a stationary camera and on a motion of an object. We ca derive the necessary and sufficient condition that an image sequence consists of the projection of the periodic motion by the affine transformation that is a reasonally good approach to the perspective projection. The difficulty of detecting its periodic motion is to select its have period in sequence and to define its width.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.265-274
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• 2012

In this paper, we propose a method for preceding vehicle detection and tracking with motion estimation by radar-vision sensor fusion. The motion estimation proposed results in not only correction of inaccurate lateral position error observed on a radar target, but also adaptive detection and tracking of a preceding vehicle by compensating the changes in the geometric relation between the ego-vehicle and the ground due to the driving. Furthermore, the feature-based motion estimation employed to lessen computational burden reduces the number of deployment of the vehicle validation procedure. Experimental results prove that the correction by the proposed motion estimation improves the performance of the vehicle detection and makes the tracking accurate with high temporal consistency under various road conditions.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.147-153
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• 2015

We propose a detecting method for a car accident in parking lots. The proposed method consists of 3 parts : car detection, car tracking, and accident detection. In the car detection part, we detect the car using the pixel based foreground extraction method and the motion map. From the result of the car detection, the moving car is tracked. In the accident detection part, we set the accident detecting region in front of car, and then the car accident is detected using the difference of the motion. Experimental results show that the proposed method effectively detects the car accident in the parking lots.