Title :
A review on pedestrian detection techniques based on Histogram of Oriented gradient feature
Author :
Chi Qin Lai ; Soo Siang Teoh
Author_Institution :
Sch. of Electr. & Electron. Eng., Univ. Sains Malaysia, Nibong Tebal, Malaysia
Abstract :
Locally normalized Histogram of Oriented Gradient (HOG) algorithm originally proposed by Dalal & Triggs presents excellent results for pedestrian detection. However, as the demand of accuracy and speed in real-time application increase, the detection speed and robustness of this method is becoming insufficient. Over the years, improvements have been proposed by different researchers in order to meet the requirement of the robustness and processing speed. This includes the improvement in the ways HOG feature is extracted, combination of HOG feature with other image features and using part based detection method. This paper reviews the current advancement in HOG features for human detection.
Keywords :
feature extraction; gradient methods; object detection; pedestrians; traffic engineering computing; HOG algorithm; HOG feature extraction; histogram of oriented gradient feature; human detection; image features; locally normalized histogram of oriented gradient algorithm; part based detection method; pedestrian detection techniques; real-time application; Accuracy; Feature extraction; Graphics processing units; Histograms; Robustness; Support vector machine classification; Advanced Driver Assistance System; HOG Feature; Human Detection; Object Classification; Pedestrian Detection;
Conference_Titel :
Research and Development (SCOReD), 2014 IEEE Student Conference on
Print_ISBN :
978-1-4799-6427-7
DOI :
10.1109/SCORED.2014.7072948
