Vehicle Tracking Systems Research Papers (original) (raw)

Top Papers
Most Cited Papers
Most Downloaded Papers
Newest Papers
People
- by
- •
- Engineering, Data Mining, Intelligent Transportation Systems, Mobility
- by Lee D. Han
- •
- Bioinformatics, Natural Language Processing, Machine Learning, Data Mining
- by Aaron Weinberg
- •
- Biomedical Engineering, Telecommunications, Performance, Technological forecasting

In this paper we are interested in analyzing behaviour in crowded public places at the level of holistic motion. Our aim is to learn, without user input, strong scene priors or labelled data, the scope of "normal behaviour" for a particular scene and thus alert to novelty in unseen footage. The first contribution is a low-level motion model based on what we term tracklet primitives, which are scene-specific elementary motions. We propose a clustering-based algorithm for tracklet estimation from local approximations to tracks of appearance features. This is followed by two methods for motion novelty inference from tracklet primitives: (a) an approach based on a non-hierarchial ensemble of Markov chains as a means of capturing behavioural characteristics at different scales, and (b) a more flexible alternative which exhibits a higher generalizing power by accounting for constraints introduced by intentionality and goal-oriented planning of human motion in a particular scene. Evaluated on a 2h long video of a busy city marketplace, both algorithms are shown to be successful at inferring unusual behaviour, the latter model achieving better performance for novelties at a larger spatial scale.

Large cities with fleet of vehicles require a system
to determine location of movement of passenger vehicles at a
given time. Vehicle tracking systems can be used in theft
prevention, retrieval of lost vehicles, providing trafricoriented
services on lanes. The Vehicle tracking systems
VETRAC enables vehicle drivers or any third party to track
the location of any moving vehicle. Most modern vehicle
tracking systems use GPS[71 modules which is costly in usage
and implementation. Many systems also combine a
communications component such as cellular or satellite
transmitters to communicate the vehicle's location to a
remote user. VETRAC uses WiFi IEEE 802.11 b/g for easy
and accurate location of the vehicle, which provides effective
and simple communication. Vehicle information can be
viewed on electronic maps using the Internet or specialized
software. We have designed and developed an Intelligent
Vehicle Navigation System, which identify an optimally
minimal path for navigation with minimal traffic intensity
using WiFi. The system can also be used as a city guide to
locate and identify landmarks in a new city.

Our aim is to estimate the perspective-effected geometric distortion of a scene from a video feed. In contrast to most related previous work, in this task we are constrained to using low-level, spatio-temporally local motion features only. This particular challenge arises in many semi-automatic surveillance systems which alert a human operator to potential abnormalities in the scene. Low-level, spatio-temporally local motion features are sparse (and thus require comparatively little storage space) and sufficiently powerful in the context of video abnormality detection to reduce the need for human intervention by more than 100-fold. This paper introduces three significant contributions: (i) we describe a dense algorithm for perspective estimation which uses motion features to estimate the perspective distortion at each image locus and then polls all such local estimates to arrive at the globally best estimate, (ii) we also present an alternative coarse algorithm which subdivides the image frame into blocks, and uses motion features to derive block-specific motion characteristics and constrain the relationships between these characteristics, with the perspective estimate emerging as a result of a global optimization scheme, and (iii) we report the results of an evaluation using nine large sets acquired using existing close-circuit television (CCTV) cameras, not installed specifically for the purposes of this work. Our findings demonstrate that both of the proposed methods are successful, their accuracy matching that of human labelling using complete visual data (by the constraints of the setup unavailable to our algorithms).

- by Krishna Pattipati
- •
- Modeling, Trajectory, Tracking, Vehicle Tracking Systems
- by Chun-yi Su
- •
- Engineering, Adaptive Control, Stability, Mathematical Sciences

The need to estimate a particular quantile of a distribution is an important problem which frequently arises in many computer vision and signal processing applications. For example, our work was motivated by the requirements of many semi-automatic surveillance analytics systems which detect abnormalities in close-circuit television (CCTV) footage using statistical models of low-level motion features. In this paper we specifically address the problem of estimating the running quantile of a data stream when the memory for storing observations is limited. We make several major contributions: (i) we highlight the limitations of approaches previously described in the literature which make them unsuitable for non-stationary streams, (ii) we describe a novel principle for the utilization of the available storage space, (iii) we introduce two novel algorithms which exploit the proposed principle in different ways, and (iv) we present a comprehensive evaluation and analysis of the proposed algorithms and the existing methods in the literature on both synthetic data sets and three large real-world streams acquired in the course of operation of an existing commercial surveillance system. Our findings convincingly demonstrate that both of the proposed methods are highly successful and vastly outperform the existing alternatives. We show that the better of the two algorithms (data-aligned histogram) exhibits far superior performance in comparison with the previously described methods, achieving more than 10 times lower estimate errors on real-world data, even when its available working memory is an order of magnitude smaller.

- by Ognjen Arandjelovic
- •
- Engineering, Applied Mathematics, Computer Science, Algorithms

An integrated GPS-GSM system is proposed to track vehicles using Google Earth application. The remote module has a GPS mounted on the moving vehicle to identify its current position, and to be transferred by GSM with other parameters acquired by the automobile’s data port as an SMS to a recipient station. The received GPS coordinates are filtered using a Kalman filter to enhance the accuracy of measured position. After data processing, Google Earth application is used to view the
current location and status of each vehicle. This goal of this system is to manage fleet, police automobiles distribution and car theft cautions.

This paper describes a new way of providing security for objects; the object can either be a file or an automotive like car, etc. The method used for providing security to objects is by creating a virtual fence around the object in such a way that whenever the object is moved out of the fence it is considered as an event and the event is notified to the user. Encryption is one of the techniques for providing security to objects, and the key used for encryption plays major role in providing security. This paper explains a new way of key generation which makes the file to be decrypted at the same location and by the same person (who knows the password) where it is encrypted, and the decrypted file is deleted whenever the fence is exited. This paper also explains a method for providing security to automobile by creating a fence around the vehicle. The engine automatically locks whenever the fence is exited and when the vehicle is used by an unauthorized person.

This paper is about the detection of traffic rule breach via computer vision which takes the feed from the traffic surveillance system, processes the video feed, detects the breach and alerts the traffic police. The number of traffic accidents is on the rise with the increasing number of vehicles. Traffic breach is the biggest cause of accidents. So, to mitigate this problem our system processes the CCTV camera feed in real-time, detects the traffic rule breach events and sends the push notification to the android based application of the traffic police stationed nearby; so, further actions can be taken. As this system detects breach faster than humans, the concerned authoritarian department will be at ease in implementing safe roads accurately. This system acts as an add-on to the current video surveillance system rather than building new infrastructure. Thus, the output of this system can be used not only or safety and security purposes but as well as for analytical purposes with effective traffic monitoring at a lower cost. Hence, this system aids law enforcement agencies in implementing road safety efficiently and effectively ensuring smooth traffic flow.

- by Sunim Acharya and +2
- •
- Image Processing, Surveillance, Image Classification, Vehicle Tracking Systems

Traffic accidents, one of the leading sources of deaths in all places. This paper gives alert before the situation is in danger and immediately shares the location where the accident occurred. The alert will be given when the driver is not in the condition to drive and location is traced) using GPS (Global Positioning System) once accident occurred. This system helps to trace the vehicle's location easily and alerts the driver when he consumed alcohol and feels sleepy and also it helps in avoiding accidents and to provide the necessary help as soon as possible after the accident happens.

In the current scenario, there are problems during travelling like too heavy to drive the luggage, chances of missing and unauthorized accessing and charging mobile or laptop .So, the self-driving luggage helps their owner during travelling or help to overcome from the problems during travelling such solutions are the luggage follow their owner, tracking system, digital locking system and charging port in the luggage.

- by IJRASET Publication
- •
- Vehicle Tracking Systems, Authorization

A linear state-space model is described whose second-order moments match that of a hidden Markov chain. This model enables a modified transition probability matrix to be employed within minimum-variance filters and smoothers. However, the ensuing filter/smoother designs can exhibit suboptimal performance because a previously-reported transition-probability-matrix modification is conservative, and identified models can lack observability and reachability. This paper describes a less-conservative transition-probability-matrix modification and a model-order-reduction procedure to enforce observability and reachability. An optimal minimum-variance predictor, filter and smoother are derived to recover the Markov chain states from noisy measurements. The predictor is asymptotically stable provided that the problem assumptions are correct. It is shown that collapsing the model improves state prediction performance. The filter and smoother recover the Markov states exactly when the measurement noise is negligible. A mining vehicle position tracking application is discussed in which performance benefits are demonstrated.

- by G. Einicke
- •
- Estimation and Filtering Theory, GPS Applications, Kalman Filter, Navigation

Vehicle detection and tracking is an inevitable application of visual surveillance. There are several techniques in the literature which deal with vehicle detection, but the decrease in visibility due to camera noise and unfavourable climatic conditions due to snow, fog, rain, swaying leaves etc. makes it difficult to detect the moving objects in the scene. This paper
proposes a framework to detect and track multiple moving vehicles despite of occlusions. To detect and segment the moving vehicles make use of dynamically adaptive threshold using the modified full-search sum of absolute difference algorithm, which reduces computational complexity. For tracking all the detected objects uniquely, an algorithm using Kalman filter is proposed, which is able to handle occlusions to a greater extend.

- by Sukanyathara J
- •
- Computer Vision, Digital Image Processing, Vehicle Tracking Systems