In this project, I develop an approach to post process local pedestrian detection by incorporating cues from the background. This approach uses a combination of several location specific color classifiers to quickly reduce the number of the local detector responses by discarding improbable results. An experimental method for color comparison is explored in this project to supplement existing te...

Recently, pedestrian detection from in-vehicle camera images is becoming an important technology in ITS (Intelligent Transportation System). However, it is difficult to detect pedestrians stably due to the variety of their poses and their backgrounds. To tackle this problem, we propose a method to detect various pedestrians from in-vehicle camera images by using multiple classifiers correspondi...

6 This paper presents a module for pedestrian detection from a 7 moving vehicle in low-light conditions. The algorithm make 8 use of a single far infrared camera based on a microbolometer. 9 Images of the area ahead of the vehicle are analyzed 10 to determine if any pedestrian might be in its trajectory. 11 Detection is achieved by searching for distributions of 12 temperatures in the scene sim...

Detection of human beings with accuracy in visual surveillance systems is important for various application areas like remote and mobile monitoring, traffic monitoring, public safety and abnormal event detection. The first step in detection process is to detect the object which is in motion and further classify it and track the objects. The paper further directs towards the detection and tracki...

Nowadays, pedestrian recognition in far-infrared images toward realizing a night vision system becomes a hot topic. However, sufficient performance could not be achieved by conventional schemes for pedestrian recognition in farinfrared images. Since the properties of far-infrared images are different from visible images, it is not known what kind of scheme is suitable for pedestrian recognition...

In this paper, we present a system framework for event detection in pedestrian and tracking applications. The system is built upon a robust computer vision approach to detecting and tracking pedestrians in unconstrained crowded scenes. Upon this framework we propose a pedestrian indexing scheme and suite of tools for detecting events or retrieving data from a given scenario.

Observation in absolute darkness and daytime under every atmospheric situation is one of the advantages of thermal imaging systems. In spite of increasing trend of using these systems, there are still lots of difficulties in analysing thermal images due to the variable features of pedestrians and atmospheric situations. In this paper an efficient method is proposed for detecting pedestrians in ...

Object detection and classification is challenging problem for vision-based intersection monitoring since traditional motion-based techniques work poorly when pedestrians or vehicles stop due to traffic signals. In this work, we present a method for vehicle and pedestrian recognition at intersections that benefits from both motion and appearance cues in video surveillance. Vehicle and pedestria...

In this paper we introduce Context-Sensitive Decision Forests A new perspective to exploit contextual information in the popular decision forest framework for the object detection problem. They are tree-structured classifiers with the ability to access intermediate prediction (here: classification and regression) information during training and inference time. This intermediate prediction is av...

This article discusses a pedestrian detector for an experimental vehicle, based on visual information from a single far infrared camera. The system considers three consecutive processes for each image. Once the candidates’ heads have been extracted, regions of interest are resized based on the distance to the camera and then filtered by its vertical edges symmetry. Once the bounding boxes of po...