Study of Different Approaches of Creature Detection in DIP

Creature identification assumes a critical part in everyday life. In the region like an air terminal where the nearness of any sort of creature nearness is entirely confined, creature location assumes an exceptionally fundamental part in such territories. In the horticultural regions put close to the timberland numerous creatures demolishes the harvests or even assault on individuals hence there is a need of framework which identifies the animal nearness and gives cautioning about that in the perspective of security reason. What's more, it is additionally helpful in the timberlands. Where wild animal can distinguish for the wellbeing reason.

Animal Detection using Background Subtraction & Blob Detection Technique

Animal detection plays an important role in day to day life due to its impact on the human life directly or indirectly. In the area like an airport where the presence of any kind of animal is strictly restricted, animal detection tool can play an important role in such areas. In this work, the performance of different image features and classification algorithms in animal detection application, and design a real-time animal detection system following criteria in terms of accuracy, time and cost of computation is explored. To follow these qualities, detection process is done in two levels. In first level, bulb detection process is used to subtract background from the image and this image is used in second stage for finding the region of the object using regionpropos algorithm. To examine the animal detection system, we created our own dataset, this dataset can be updated according to the application or use. The result of the approach shows that we can successfully detect the animal when it comes in a particular background

Extended Object Tracking: Introduction, Overview and Applications

This article provides an elaborate overview of current research in extended object tracking. We provide a clear definition of the extended object tracking problem and discuss its delimitation to other types of object tracking. Next, different aspects of extended object modelling are extensively discussed. Subsequently, we give a tutorial introduction to two basic and well used extended object tracking approaches - the random matrix approach and the Kalman filter-based approach for star-convex shapes. The next part treats the tracking of multiple extended objects and elaborates how the large number of feasible association hypotheses can be tackled using both Random Finite Set (RFS) and Non-RFS multi-object trackers. The article concludes with a summary of current applications, where four example applications involving camera, X-band radar, light detection and ranging (lidar), red-green-blue-depth (RGB-D) sensors are highlighted.Comment: 30 pages, 19 figure

Simultaneous Tracking and Shape Estimation of Extended Objects

This work is concerned with the simultaneous tracking and shape estimation of a mobile extended object based on noisy sensor measurements. Novel methods are developed for coping with the following two main challenges: i) The computational complexity due to the nonlinearity and high-dimensionality of the problem, and ii) the lack of statistical knowledge about possible measurement sources on the extended object

Tracking Extended Objects with Active Models and Negative Measurements

Extended object tracking deals with estimating the shape and pose of an object based on noisy point measurements. This task is not straightforward, as we may be faced with scarce low-quality measurements, little a priori information, or we may be unable to observe the entire target. This work aims to address these challenges by incorporating ideas from active contours and exploiting information from negative measurements, which tell us where the target cannot be

Tracking Extended Objects in Noisy Point Clouds with Application in Telepresence Systems

We discuss theory and application of extended object tracking. This task is challenging as sensor noise prevents a correct association of the measurements to their sources on the object, the shape itself might be unknown a priori, and due to occlusion effects, only parts of the object are visible at a given time. We propose an approach to track the parameters of arbitrary objects, which provides new solutions to the above challenges, and marks a significant advance to the state of the art