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Pedestrian detection is an important topic in many applications, such as intelligent transportation systems (ITSs) or surveillance. For the purpose of applications used around the clock, the work for detecting pedestrian based on thermal sensors has attracted significant attention. To achieve this, this paper proposes a LBP (local binary pattern) encoded multi-level classifier for detecting pedestrians...
Detecting pedestrians is a challenging problem owing to the motion of the subjects, the camera and the background and to variations in pose, appearance, clothing, illumination and background clutter. The Region Covariance Matrix (RCM) descriptors show experimentally significantly out-performs existing feature sets for pedestrian detection. In this paper, we present an efficient features extraction...
Good performance of pedestrian detection in an automatic driving system is a necessary task. Many pedestrian detection algorithm use Histogram Oriented Gradient (HOG) for feature extraction and Support Vector Machine (SVM) for classification. Some papers use additional features with HOG, such as Local Binary Pattern (HOG-LBP), to improve the performance. Neural Network and Extreme Learning Machine...
This paper proposes a Network Shaped Cascade Classifier(NSCC) based on potential functions for pedestrian detection. Potential function is exploited to capture the nonlinear information in the training set based on the multiple sample centers. A flexible structure in NSCC is used to combine the base classifier and potential function into a nonlinear cascade classifier, and NSCC can well inherit the...
This paper presents an omnidirectional vision based solution to detect human beings. We first go through the conventional sliding window approaches for human detection. Then, we describe how the feature extraction step of the conventional approaches should be modified for a theoretically correct and effective use in omnidirectional cameras. In this way we perform human detection directly on the omnidirectional...
The Pedestrian detection using Histograms of Oriented Gradients (HOG) is the most popular method to detect a human from a picture. However, it, calculates the HOG description, will cost too much time and can't meet the real-time request for detecting pedestrian from the video surveillance system. In this paper we present a novel algorithm for detecting a human from a video. Firstly, The improved approach...
Pedestrian detection plays important roles in various applications such as automobile driving assistance and surveillance camera system. The co-occurrence histograms of oriented gradients (CoHOG) feature descriptor showed good performance since thirty co-occurrences at each pixel position represent various spatial characteristics of object shapes. Though extraction of co-occurrence histogram features...
We investigate pedestrian detection in depth images. Unlike pedestrian detection in intensity images, pedestrian detection in depth images can reduce the effect of complex background and illumination variation. We propose a new feature descriptor, Histogram of Depth Difference(HDD), for this task. The proposed HDD feature descriptor can describe the depth variance in a local region as Histogram of...
This paper presents a fast and accurate pedestrian detection method. To find a balance between speed and accuracy, we propose a Multi-Pose Learning Boosted Integrable Features Pool (MPL-Boosted IFP) approach. Our method achieves high recall-rate while taking the speed-advantage of cascade-of-rejectors approach. We build different types of feature sets, in which features are extremely fast to compute...
This paper presents a novel approach in pedestrian detection in static images. The state-of-art feature named histograms of oriented gradients (HOG) is adopted as the basic feature which we modify and create a new feature using boosting algorithm. The detection is achieved by training a linear SVM with the boosted HOG feature. We experimentally demonstrate that our solution achieve comparable performance...
This paper considers pedestrian detection, specialized for a near infrared imaging system at night. The main objective is the detection of a distant pedestrian, beyond an illuminated area in a low-beam mode, using a monocular on-board camera. In this method, the region of interest (ROI) is first selected by extracting bright regions, and shape information from a whole human body, is later used for...
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