A Traffic Surveillance System using Dynamic Saliency Map and SVM Boosting

이민호,이정우,이우노 제어·로봇·시스템학회 2010 International Journal of Control, Automation, and Vol.8 No.5

This paper proposes a traffic surveillance system that can efficiently detect an interesting object and identify vehicles and pedestrians in real traffic situations. The proposed system consists of a moving object detection model and an object identification model. A dynamic saliency map is used for analyzing dynamics of the successive static saliency maps, and can localize an attention area in dy-namic scenes to focus on a specific moving object for traffic surveillance purposes. The candidate local areas of a moving object are followed by a blob detection processing including binarization, morphological closing and labeling methods. For identifying a moving object class, the proposed system uses a hybrid of global and local information in each local area. Although the global feature analysis is a compact way to identify an object and provide a good accuracy for non-occluded objects, it is sensitive to image translation and occlusion. Therefore, a local feature analysis is also considered and combined with the global feature analysis. In order to construct an efficient classifier using the global and local features, this study proposes a novel classifier based on boosting of support vector machines. The proposed object identification model can identify a class of moving object and discard unexpected candidate area which does not include an interesting object. As a result, the proposed road surveillance system is able to detect a moving object and identify the class of the moving object. Experimental results show that the proposed traffic surveillance system can successfully detect specific moving objects.

Detection and Tracking of Moving Objects with a Laser Scanner on a Grid Map for an Autonomous Vehicle

Dongchul Kim,Jaehyun Han,Minchae Lee,Myoungho Sunwoo 한국자동차공학회 2009 한국자동차공학회 학술대회 및 전시회 Vol.2009 No.11

Environmental perception such as obstacle detection and tracking is an inevitable requirement for autonomous vehicles. Especially, in order to avoid collisions, autonomous vehicles require a detection and tracking of moving objects (DATMO) such as vehicles and pedestrians. The multiple hypothesis approach (MHA) is most frequently used for DATMO, whereby the MHA generates all possible hypotheses for moving objects. However, the MHA also generates hypotheses for immobile objects such as parked vehicles, bushes, and trees, among others, the result of which is a computational overhead for DATMO as a result of tracking irrelevant hypotheses. The ability to distinguish moving objects from static objects using a laser scanner with an occupancy grid map has been developed previously. In the present study, we utilized this method in order to apply MHA to only moving objects. Using this approach, moving objects were efficiently detected and tracked on a grid map. Furthermore, DATMO on the grid map was effectively implemented in real-time.

Detection and Recognition of Moving Objects using the Moving Mask Method and the Hidden Markov Model

조완현,김선월,안국동 한국자료분석학회 2011 Journal of the Korean Data Analysis Society Vol.13 No.1

This paper proposes a new detection and recognition method for moving objects that uses the moving mask method and the hidden Markov model. First, we apply the concept of entropy to convert the pixel value in the image domain into the amount of energy change in the entropy domain. Second, we find the coarse region of moving objects by automatically generating the moving mask image from the inter-frame difference between two transformed entropy images. Third, we use the discrete wavelet transformation technique to extract proper feature vectors from the detected mask image. Fourth, we use the hidden Markov model to accurately recognize moving objects. The results indicate that our proposed method can effectively and accurately detect and recognize moving objects in image sequences.

Extraction of Effective Motion Vectors Based on Morphological Feature and Thinning Algorithm

김재호,김윤호 한국정보기술학회 2016 JOURNAL OF ADVANCED INFORMATION TECHNOLOGY AND CON Vol.6 No.1

This research proposed an algorithm conducting context awareness and tracking of a moving object. The research process is as follows: First, this study carried out preprocessing, such as binary coding, noise elimination and opening-closing arithmetic operations, after acquiring background subtraction image using BSM for moving object extraction. Second, this research eliminated the shadow of a moving object using three characteristics, namely chromatic image, brightness change and shadow direction in order to eliminate shadows, which a negative factor for image analysis. Third, this research calculated the skeleton line of a moving object by applying the thinning algorithm. Then, this research perceived the rapidly changing context of the moving object using the slope of the skeleton line. Lastly, the center point of the moving object was found by applying the pruning algorithm to the skeleton line, while it created moving direction and moving trajectory by comparing each frame central point of the moving object. As a result of the experiment, the rapid movement change of a moving object was extracted, and the moving direction was found through a central point comparison, while the method proposed by creating a moving trajectory was confirmed to be valid.

이동체 데이타베이스에서 도로 네트워크를 이용한 불확실 위치데이타의 질의처리

안성우(Sungwoo Ahn),안경환(Kyunghwan An),배태욱(Taewook Bae),홍봉희(Bonghee Hong) 한국정보과학회 2006 정보과학회논문지 : 데이타베이스 Vol.33 No.3

TPR-tree는 시간 함수 기반의 색인으로 위치 좌표와 속도 벡터 정보를 이용하여 이동체의 위치를 표현함으로써 현재 및 미래 위치 예측을 위한 질의에 사용된다. 그러나 이동체의 이동방향 및 속도가 특정 임계값을 벗어날 경우 매번 서버에 새로운 위치를 보고하기 때문에 차량과 같이 이동방향과 속도가 빈번하게 변하는 환경에 적용할 경우 서버로의 잦은 보고를 필요로 하게 되어 통신비용을 크게 증가시키는 문제가 있다. 통신비용을 일정하게 유지하기 위해서 이동체의 위치 보고를 일정한 시간 간격으로 수행하게 하는 방법이 있다. 그러나 일정한 시간 간격으로 보고되는 이동체의 위치를 저장하는 경우 보고 간격 사이에 속도와 방향이 변하게 되면 시간에 대한 선형적인 위치 예측 시에 오차가 발생하는 문제가 있다. 이 논문에서는 일정한 시간 간격으로 이동체의 위치보고가 이루어질 때 속도와 방향의 불확실성을 반영하여 이동체의 위치 예측을 위해 도로네트워크 정보를 적용한 질의 처리 기냅 및 데이타 저장 구조를 제시한다. 제시된 기법은 도로 네트워크 정보를 이용하여 이동체의 이동 방향을 도로 네트워크 세그먼트의 방향으로 제한함으로써 불확실 영역을 감소시키고 있으며 도로 네트워크 세그먼트의 종류벼리로 최대 속도를 설정하여 이동 속도의 변화에 대한 불확실성을 제거한다. 실험결과를 통하여 제안된 질의 처리 기법이 미래 위치에 대한 영역 질의 시에 False miss를 발생시키지 않으면서 False hit를 최소화 시키는 것을 확인함으로써 TPR-tree를 이용한 기존의 질의 처리 기법보다 질의 영역의 크기에 따라 최대 60% 이상 위치 예측 정확도가 향상됨을 알 수 있다. The TPR-tree is the time-parameterized indexing scheme that supports the querying of the current and projected future positions of such moving objects by representing the locations of the objects with their coordinates and velocity vectors. If this index is, however, used in environments that directions and velocities of moving objects, such as vehicles, are very often changed, it increases the communication cost between the server and moving objects because moving objects report their position to the server frequently when the direction and the velocity exceed a threshold value. To preserve the communication cost regularly, there can be used a manner that moving objects report their position to the server periodically. However, the periodical position report also has a problem that linear time functions of the TPR-tree do not guarantee the accuracy of the object's positions if moving objects change their direction and velocity between position reports. To solve this problem, we propose the query processing scheme and the data structure using road networks for predicting uncertainty positions of moving objects, which is reported to the server periodically. To reduce an uncertainty of the query region, the proposed scheme restricts moving directions of the object to directions of road network's segments. To remove an uncertainty of changing the velocity of objects, it puts a maximum speed of road network segments. Experimental results show that the proposed scheme improves the accuracy for predicting positions of moving objects than other schemes based on the TPR-tree.

Research on detecting moving targets with an improved Kalman filter algorithm

Jia quan Zhou,Wei Wei 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.9

As science and technology evolve, object detection of moving objects has been widely used in the context of machine learning and artificial intelligence. Traditional moving object detection algorithms, however, are characterized by relatively poor real-time performance and low accuracy in detecting moving objects. To tackle this issue, this manuscript proposes a modified Kalman filter algorithm, which aims to expand the equations of the system with the Taylor series first, ignoring the higher order terms of the second order and above, when the nonlinear system is close to the linear form, then it uses standard Kalman filter algorithms to measure the situation of the system. which can not only detect moving objects accurately but also has better real-time performance and can be employed to predict the trajectory of moving objects. Meanwhile, the accuracy and real-time performance of the algorithm were experimentally verified.

이동 객체 데이타베이스에서 KDB-tree의 동적 분할 정책

임덕성(Duksung Lim),이창헌(Changheun Lee),홍봉희(Bonghee Hong) 한국정보과학회 2006 정보과학회논문지 : 데이타베이스 Vol.33 No.4

Moving object databases manage a large amount of past location data which are accumulated as the time goes. To retrieve fast the past location of moving objects, we need index structures which consider features of moving objects. The KDB-tree has a good performance in processing range queries. Although we use the KDB-tree as an index structure for moving object databases, there has an over-split problem in the spatial domain since the feature of moving object databases is to increase the time domain. Because the over-split problem reduces spatial regions in the MBR of nodes inverse proportion to the number of splits, there has a problem that the cost for processing spatial-temporal range queries is increased. In this paper, we propose the dynamic split strategy of the KDB-tree to process efficiently the spatial-temporal range queries. The dynamic split strategy uses the space priority splitting method for choosing the split domain, the recent time splitting policy for splitting a point page to maximize the space utilization, and the last division policy for splitting a region page. We compare the performance of proposed dynamic split strategy with the 3DR-tree, the MV3R-tree, and the KDB-tree. In our performance study for range queries, the number of node access in the MKDB-tree is average 30% less than compared index structures. 시간의 흐름에 따라 누적되는 대용량의 과거 위치를 관리하는 이동 객체 데이타베이스에서 이동 객체의 과거 위치를 효율적으로 검색하기 위해서는 이동 객체의 특성을 고려한 색인 구조가 필요하다. 그러나, 영역 질의 성능이 우수한 다차원 색인인 KDB-tree를 이동 객체 데이타베이스에 적용할 경우 시간 도메인이 증가하는 이동 객체 데이타베이스의 특성으로 인해 공간 도메인 가중 분할이 발생한다. 공간도메인 가중 분할은 하나의 노드가 차지하는 MBR의 공간 영역이 분할 횟수에 반비례하게 감소되어 시공간 영역 질의 처리시 색인의 검색 비용을 증가시키는 문제가 있다. 이 논문에서는 이동 객체 데이타베이스에서 시공간 영역 질의를 효율적으로 처리하기 위한 KDB-tree의 동적 분할 정책을 제안한다. 동적 분할 정책은 공간 우선 분할 방법을 적용하는 분할 도메인 선정 방법과 포인터 페이지에서 공간 활용도를 최대화 시킬 수 있는 최근 시간 분할 정책, 영역 페이지에서 적용되는 최후 시간 분할 정책으로 구성된다. 제안한 동적 분할 정책의 성능을 평가하기 위해 3DR-tree, MV3R-tree, KDB-tree와의 성능을 비교한다. 영역 질의를 위한 성능 평가에서 동적 분할 정책을 적용한 MKDB-tree는 기존 색인에 비해 평균 30%이상의 노드 접근 회수를 감소시킨다.

Adaptive Cell-Based Index For Moving Objects In Indoor

( Soongsun Shin ),( Gyoungbae Kim ),( Haeyoung Bae ) 한국인터넷정보학회 2012 KSII Transactions on Internet and Information Syst Vol.6 No.7

Existing R-tree that is based on a variety of outdoor-based techniques to manage moving objects have been investigated. Due to the different characteristics of the indoor and outdoor, it is difficult to management of moving object using existed methods in indoor setting. We propose a new index structure called ACII(adaptive Cell-based index for Indoor moving objects) for Indoor moving objects. ACII is Cell-based access structure adopting an overlapping technique. The ACII refines cells adaptively to handle indoor regional data, which may change its locations over time. The ACII consumed at most 30% of the space required by R-tree based methods, and achieved higher query performance compared with r-tree based methods.

이동체의 위치 정보를 저장하기 위한 해쉬 기반 색인의 성능 분석

전봉기(Bong-Gi Jun) 한국컴퓨터정보학회 2006 韓國컴퓨터情報學會論文誌 Vol.11 No.6

이동체 데이터베이스 시스템은 연속적으로 위치와 방향을 바꾸는 이동체 집합을 관리해야 한다. 전통적인 공간색인 기법은 정적인 공간 데이터를 관리하는 목적으로 사용되기 때문에 이동체를 위한 색인으로 부적합하다. 이동체의 위치는 연속적으로 변하기 때문에, 이동체의 색인은 변경된 위치 정보를 유지하기 위하여 빈번한 갱신 연산을 수행해야 한다. 이 논문에서는 이동체들의 이동을 처리하기 위한 삽입/삭제 비용을 분석하였다. 실험 결과에서 제안하는 동적 해싱 색인이 기존의 R-트리와 고정 그리드 보다 성능이 우수하였다. Moving objects database systems manage a set of moving objects which changes its locations and directions continuously. The traditional spatial indexing scheme is not suitable for the moving objects because it aimed to manage static spatial data. Because the location of moving object changes continuously, there is problem that expense that the existent spatial index structure reconstructs index dynamically is overladen. In this paper, we analyzed the insertion/deletion costs for processing the movement of objects. The results of our extensive experiments show that the Dynamic Hashing Index outperforms the original R-tree and the fixed grid typically by a big margin.

모바일 응용에서 이동 객체의 궤적-기반 질의를 위한 색인 구조

심춘보,주재흠,Shim Choon-Bo,Joo Jae-Heum 한국정보통신학회 2004 한국정보통신학회논문지 Vol.8 No.8

With the rapid development of wireless communications and mobile technologies, requirements of various services based on moving objects like location-based services and mobile applications services have been increased. In this paper, we propose an index structure which can improve the performance on trajectory-based query especially, one of the various query types for moving objects in mobile applications. It maintains link table(L-Table) to obtain good efficiency on retrieval and insertion performance of the existing TB(Trajectory Bundle)-tree proposed for trajectory-based query of moving objects. The L-Table contains page number in disk and memory pointers pointing the leaf node with the first and last line segment of moving objects in order to directly access preceding node. In addition, we design to reside a part of whole index in main memory by preserving a fixed size of buffer in case of being restricted by available main memory. Finally, experimental results with various data sets show that the proposed technique is superior to the existing index structures with respect to insertion and trajectory-based query. 무선 통신 및 모바일 기술의 급속한 발전으로 인해 위치 기반 서비스 및 모바일 응용 서비스와 같은 이동 객체에 기반한 다양한 서비스에 대한 요구가 증가하게 되었다. 이를 위해, 본 논문에서는 모바일 응용에서 이동 객체에 대한 다양한 질의 중에서 특히 궤적-기반 질의에 대한 성능을 향상시킬 수 있는 색인 구조를 제안한다. 제안하는 색인 구조는 이동 객체의 궤적-기반 질의를 위해 제안되었던 기존의 TB-tree의 삽입 및 검색 성능의 효율성을 높이기 위해 연결테이블(LinkTable:L-Table)을 유지한다. L-Table은 선행 노드를 한번에 직접 접근하기 위해 이동 객체의 처음 세그먼트와 마지막 세그먼트가 저장된 단말 노드를 가리키는 포인터 정보와 디스크에서의 페이지를 가리키는 페이지 번호를 저장한다. 아울러 시스템의 가용메모리가 제약을 받는 경우에도 일정한 크기의 버퍼를 유지해 색인의 일부만을 메모리에 상주시킬 수 있도록 설계한다. 마지막으로 제안하는 색인 구조의 성능을 평가하기 위하여 다양한 실험 데이타를 이용해 성능 평가를 수행한 결과, 삽입 및 궤적-기반 질의 측면에서 기존의 색인 구조들에 비해 더 나은 성능을 보인다.