This paper proposes a multiple hypothesis tracking for multiple object tracking with moving camera. The proposed model makes use of the stability of sparse optical flow along with the invariant colour property under size and pose variation, by merging the colour property of objects into optical flow tracking. To evaluate the algorithm five different videos are selected from broadcast horse race...

− Unsupervised motion segmentation and tracking in video sequences is a complex task, requiring robust estimation and flexible modeling. The paper presents an unsupervised method of moving object segmentation and tracking in video sequences captured by static cameras. Central to our work is the nonparametric density estimation and the mean shift algorithm for finding local maxima of the probabi...

Salient object detection is an interesting subject in the field of video tracking and its applications. The main purpose of salient object detection is to estimate the position of the object in images in a continuous manner and reliably against dynamic scenes. When object is moving then its detection is a challenging task in much vision area. Two tasks are performed to detect salient object, in...

Tracking the moving objects in high traffic environment is really a complex task. For location tracking system Spatial Data values are used. The information regarding the location of the objects is maintained by Database Server. To process Spatial Query values the application server is used. Location update is the highly bandwidth and resource constrained operation in the moving object tracking...

1. Introduction Detecting moving objects in a video sequence and object tracking are indispensable technologies for surveillance and recognition systems. Various solutions have already been proposed for video object tracking (e.g. background difference based method [1], optical flow based method, and model-based method). However, each method has some short comings, for example, although the bac...

Automated motion detection and tracking is a challenging task in traffic surveillance. In this paper, a system is developed to gather useful information from stationary cameras for detecting moving objects in digital videos. The moving detection and tracking system is developed based on optical flow estimation together with application and combination of various relevant computer vision and ima...

In this paper, a novel technique for the segmentation and tracking of moving objects is proposed. The proposed scheme extracts moving objects based on both motion and spatial information. Initially, an intra-frame segmentation is performed using a morphological segmentation algorithm. After this, the video object areas are merged according to their motions based on a new criterion. When differe...

Object tracking is a process devoted to locate the pathway of moving object in the succession of frames. The tracking of the object has been emerged as a challenging facet in the fields of robot navigation, military, traffic monitoring and video surveillance etc. In the first phase of contributions, the tracking of object is exercised by means of matching between the template and exhaustive ima...

Investigations of multiple-object tracking aim to further our understanding of how people perform common activities such as driving in traffic. However, tracking tasks in the laboratory have overlooked a crucial component of much real-world object tracking: self-motion. We investigated the hypothesis that keeping track of one's own movement impairs the ability to keep track of other moving obje...

We present a 3D object tracking method using a single depth camera for Spatial Augmented Reality (SAR). The drastic change of illumination in a SAR environment makes object tracking difficult. Our method uses a depth camera to train and track the 3D physical object. The training allows maker-less tracking of the moving object under illumination changes. The tracking is a combination of feature ...