• Yasmeen Kasam Mulla

Due to object detection is having a very close association with video analysis and understanding of different images, it has captured much attention. Existing object detection methods are based on features of images that are handcrafted and always show poor performance in the case of shallow training objects. It also not suitable for the detection of comparatively dense and small objects. Sometimes they unable to identify objects with any given geometric transformations. Their detection performance can easily show a stagnate while comparing to the high-level deeper features with the features of images of low-level In particular for the relevant circumstance, the standard surveillance system does not provide the object identification capability. The target can readily shift in diverse backgrounds with varying brightness and shadow in the conventional video object detecting system. In the case of complicated object detection, the conventional object detection system is unable to effectively identify the targets, especially in real-time. In this paper the different techniques for detection of objects are reviewed and based on the review different drawbacks and challenges has been identified to solve the problems of existing systems with respect to efficiency.

Deep learning, key frames, Object Detection, LBPH, Eigen Faces, Fisher Faces

"A Survey on Detection of Objects in Video Using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 9, page no.c460-c465, September-2022, Available :http://www.jetir.org/papers/JETIR2209276.pdf

"A Survey on Detection of Objects in Video Using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 9, page no. ppc460-c465, September-2022, Available at : http://www.jetir.org/papers/JETIR2209276.pdf