In this paper, we propose a pedestrian detection algorithm based on both appearance and motion features to achieve high detection accuracy when applied to complex scenes. Here, a pedestrian’s appearance is described by a histogram of oriented spatial gradients, and his/her motion is represented by another histogram of temporal gradients computed from successive frames. Since pedestrians typical...

In this paper, we present a new pedestrian detection method combining Random Forest and Dominant Orientation Templates(DOT) to achieve state-of-the-art accuracy and, more importantly, to accelerate run-time speed. DOT can be considered as a binary version of Histogram of Oriented Gradients(HOG) and therefore provides time-efficient properties. However, since discarding magnitude information, it...

The Object detection based on histogram of oriented gradients was introduced in the context of detecting humans in images [1]. Detecting human subject in the image is a difficult task due to the fact that they appear in different appearance and poses. Thus the need to come up with a feature that allows human dorm to be detected cleanly even in cluttered background under different illumination. ...

This paper describes our participation in the Visual Privacy Task of MediaEval 2013, which aims to obscure human occurrence in image sequences. As a result the recorded person should be unrecognisable. We use an approach which pseudo-randomly scrambles pixels within specified regions. This technique is reversible and preserves the colour characteristic of each region. So, colour-based approache...

Due to the increasingly need for automatic traffic monitoring, vehicle license plate detection is of high interest to perform automatic toll collection, traffic law enforcement, parking lot access control, among others. In this paper, a sliding window approach based on Histogram of Oriented Gradients (HOG) features is used for Brazilian license plate detection. This approach consists in scannin...

Histogram of Oriented Gradients (HOG) based methods for the detection of humans have become one of the most reliable methods of detecting pedestrians with a single passive imaging camera. However, they are not 100 percent reliable. This paper presents an improved tracker for the monitoring of pedestrians within images. The Parallel HOG and Correlation Tracking (PHACT) algorithm utilises self le...

Human detection is a challenging classification problem which has many potential applications including monitoring pedestrian junctions, young children in school and old people in hospitals, and several security, surveillance and civilian applications. Various approaches have been proposed to solve this problem. We have studied and implemented a scheme using Histogram of Oriented Gradients (HOG...

Estimation of human orientation is considered a key configuration to study and understand human behaviours. There have been many works focusing on this. However, most of previous works are sensor-based technologies but visual-based technologies. In this paper, we proposed a method to estimate the orientation of human in a given image patch. We have observed the performance of a feature called H...

Descriptors based on orientation histograms are widely used in computer vision. The spatial pooling involved in these representations provides important invariance properties, yet it is also responsible for the loss of important details. In this paper, we suggest a way to preserve the details described by the local curvature. We propose a descriptor that comprises the direction and magnitude of...