Techniques for Detection and Tracking of Multiple Objects

During the past decade, object detection and object tracking in videos have received a great deal of attention from the research community in view of their many applications, such as human activity recognition, human computer interaction, crowd scene analysis, video surveillance, sports video analysis, autonomous vehicle navigation, driver assistance systems, and traffic management. Object detection and object tracking face a number of challenges such as variation in scale, appearance, view of the objects, as well as occlusion, and changes in illumination and environmental conditions. Object tracking has some other challenges such as similar appearance among multiple targets and long-term occlusion, which may cause failure in tracking. Detection-based tracking techniques use an object detector for guiding the tracking process. However, existing object detectors usually suffer from detection errors, which may mislead the trackers, if used for tracking. Thus, improving the performance of the existing detection schemes will consequently enhance the performance of detection-based trackers. The objective of this research is two fold: (a) to investigate the use of 2D discrete Fourier and cosine transforms for vehicle detection, and (b) to develop a detection-based online multi-object tracking technique. The first part of the thesis deals with the use of 2D discrete Fourier and cosine transforms for vehicle detection. For this purpose, we introduce the transform-domain two-dimensional histogram of oriented gradients (TD2DHOG) features, as a truncated version of 2DHOG in the 2DDFT or 2DDCT domain. It is shown that these TD2DHOG features obtained from an image at the original resolution and a downsampled version from the same image are approximately the same within a multiplicative factor. This property is then utilized in developing a scheme for the detection of vehicles of various resolutions using a single classifier rather than multiple resolution-specific classifiers. Extensive experiments are conducted, which show that the use of the single classifier in the proposed detection scheme reduces drastically the training and storage cost over the use of a classifier pyramid, yet providing a detection accuracy similar to that obtained using TD2DHOG features with a classifier pyramid. Furthermore, the proposed method provides a detection accuracy that is similar or even better than that provided by the state-of-the-art techniques. In the second part of the thesis, a robust collaborative model, which enhances the interaction between a pre-trained object detector and a number of particle filter-based single-object online trackers, is proposed. The proposed scheme is based on associating a detection with a tracker for each frame. For each tracker, a motion model that incorporates the associated detections with the object dynamics, and a likelihood function that provides different weights for the propagated particles and the newly created ones from the associated detections are introduced, with a view to reduce the effect of detection errors on the tracking process. Finally, a new image sample selection scheme is introduced in order to update the appearance model of a given tracker. Experimental results show the effectiveness of the proposed scheme in enhancing the multi-object tracking performance

Design, development and evaluation of a software architecture for tracking multiple vehicles in camera networks

Máster en Image Processing and Computer VisionThe free-flow portico is an automatic toll system that works thanks to the information provided by different system cameras and the use of new technologies. This work is focused on an essential part for the creation of this infrastructure, the development of the software needed to detect, classify and track targets across a network of cameras, known as multi-target multi-camera tracking, as well as the study of the hardware necessary for its deployment. First of all is to study the state of the art to understand the different methods that exist for the development of each of the tasks of this system. Afterwards, the proposal made for the selected design will be studied. This design will be formed by three cameras placed on the portico, which will be connected to a board of image processing and a strobe to provide the necessary lighting at night time. In addition to these systems it will be necessary to use a central system that will carry out the tasks of communication between the three cameras, in order to have a compact design that stores the information of each vehicle that goes through the portico. This information will contain the type of registration vehicle and the type of axles that it used. Later, the study of the hardware systems that will be used for the composition of this multicamera system will be carried out, and some of the most prominent software sections. An experimental system will be proposed for the analysis of the overall results of the system, as well as the comparison between the different proposed algorithms, in order to analyze its operations and determine which one of them is the best. This work is part of a real project that is currently being developed in INDRA, for the implementation in Spanish and international highways