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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Pedestrian And Vehicle Detection And Alert System |
| Authors Name: | Jeeva Joy , Sandhra Jolly , Swaliha Shihab , Sumesh C Raman |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_197625
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| Published Paper Id: | IJNRD2306326 |
| Published In: | Volume 8 Issue 6, June-2023 |
| DOI: | |
| Abstract: | Safety depends on the precision and real-time performance of algorithms for detecting vehicles and pedestrians in advanced driver assistance systems (ADAS).Here, a simple detection technique based on aggregated channel features (ACFs) is suggested to quickly and accurately comprehend road scenes. It consists of a context pixel ACF (CP-ACF) pedestrian detector and a multiview ACF (Mv-ACF) vehicle detector.The latter has several subclass detectors to mitigate intraclass disparities caused by different viewing angles, while the former integrates local and context information to improve robustness to pedestrian deformation.The CP-ACF pedestrian detector lowers the average miss rate (AMR) by 6.34% when compared to the original ACF.At easy, moderate, and hard levels, the Mv-ACF vehicle detector increases average precision (AP) by 40.26%.The spectrum clustering of multiview samples and the subsequent integration of these subclass detectors via confidence score calibration, which lessens vehicle intraclass differences, are responsible for this outstanding efficacy.A technique of feature sharing between pedestrian and vehicle detectors is developed to cut down on the time spent in feature extraction, which accounts for 68.8% of the total detection time.By adding road prior knowledge, a ground- plane constraints (GPCs)-based approach is proposed to control erroneous detection of pedestrians and vehicles. This approach lowers the AMR for CP- ACF pedestrian detectors by 1.07% and raises the AP for Mv-ACF vehicle detectors by an average of 0.27%.As a result, the suggested method may successfully manage erroneous detection caused by road previous information. |
| Keywords: | Pedestrian and vehicle detection, ACF, anti-deformation, multiview, |
| Cite Article: | "Pedestrian And Vehicle Detection And Alert System ", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 6, page no.d267-d272, June-2023, Available :http://www.ijnrd.org/papers/IJNRD2306326.pdf |
| Downloads: | 000118751 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2306326 Registration ID: 197625 Published In: Volume 8 Issue 6, June-2023 DOI (Digital Object Identifier): Page No: d267-d272 Country: Ernakulam, Kerala, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2306326 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2306326 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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