Realtime Object Region Detection Robust to Vehicle Headlight
نویسندگان
چکیده
منابع مشابه
Nighttime Vehicle Detection for Intelligent Headlight Control
A good visibility of the road ahead is a major issue for safe nighttime driving. However, high beams are sparsely used because drivers are afraid of dazzling others. Thus, the intelligent automatic control of vehicles’ headlight is of great relevance. It requires the detection of oncoming and preceding vehicles up to such a distance that only camera based approaches are reliable. At nighttime, ...
متن کاملNight-time Vehicle Detection for Automatic Headlight Beam Control
A clear visibility of the road ahead is significant concern for safe nighttime driving. However, high beams are utilized less than sufficient on the roads since drivers are afraid of dazzling others. Subsequently, the smart programmed control of vehicles front lamp is of incredible significance. According to road accident surveys, majority of the accidents occur in dark. Visibility in dark is s...
متن کاملRobust acoustic object detection.
We consider a novel approach to the problem of detecting phonological objects like phonemes, syllables, or words, directly from the speech signal. We begin by defining local features in the time-frequency plane with built in robustness to intensity variations and time warping. Global templates of phonological objects correspond to the coincidence in time and frequency of patterns of the local f...
متن کاملRobust object exploration and detection
In this thesis we explore models and algorithms used by an autonomous agent to find objects in the real world. We begin by tackling the problem of determining the existence and location of an object robustly given the sensors employed on an agent. Our major contribution lies in modeling the spatial correlations between the sensor and object. Next, we develop models and algorithms used to explor...
متن کاملRobust Real-time Object Detection
This paper describes a visual object detection framework that is capable of processing images extremely rapidly while achieving high detection rates. There are three key contributions. The first is the introduction of a new image representation called the “Integral Image” which allows the features used by our detector to be computed very quickly. The second is a learning algorithm, based on Ada...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Korea Multimedia Society
سال: 2015
ISSN: 1229-7771
DOI: 10.9717/kmms.2015.18.2.138