IEEE Final Year Projects on Video Processing
Video processing is a core theme across IEEE Transactions on Image Processing (TIP), IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), IEEE Transactions on Multimedia (TMM), IEEE Access, and major conferences (CVPR, ICCV, ECCV, ICIP, ICME). Final-year projects that combine classical vision with modern deep learning — detection, tracking, action recognition, learned compression, super-resolution and surveillance AI — score strongly in evaluation and industry interviews.
At ProjectsatBangalore each topic is mapped to practical tools (OpenCV, PyTorch, YOLO, FFmpeg, TensorRT, MATLAB) and supplied with IEEE base paper references, source code, metrics, university-format reports and viva support for VTU, Anna University, JNTU and autonomous colleges.
Tools & Technologies Used
Libraries, frameworks and platforms commonly required for IEEE video processing projects.
OpenCV
PyTorch
TensorFlow
YOLO / Detectron2
FFmpeg
MATLAB CV Toolbox
TensorRT / CUDA
MediaPipe
IEEE Video Processing Project Topics 2026
60+ topics inspired by IEEE Transactions, Journals, Conference Papers and IEEE Access — with domain tags, source type and tools/technologies.
| # | IEEE Video Processing Project Topic | Tools & Technologies |
|---|---|---|
| 🎯 Object Detection & Multi-Object Tracking — IEEE TIP / TCSVT / CVPR style 2026 | ||
| 01 | DetectionReal-Time Multi-Object Detection and Tracking with YOLOv8 + DeepSORT IEEE Access | YOLOv8, DeepSORT, OpenCV, PyTorch, Python |
| 02 | DetectionSmall-Object Detection in Aerial / Drone Video using Attention-Enhanced Detectors IEEE TGRS / Access | YOLOv8 / RT-DETR, PyTorch, OpenCV, VisDrone dataset |
| 03 | TrackingOcclusion-Robust Multi-Object Tracking with Re-Identification Embeddings IEEE TIP | PyTorch, FairMOT / ByteTrack, OpenCV, MOTChallenge |
| 04 | DetectionOne-Stage vs Two-Stage Detectors — Comparative Study on Custom Video Dataset IEEE Access | YOLOv8, Faster R-CNN, Detectron2, COCO metrics |
| 05 | DetectionNight-Time / Low-Light Object Detection with Image Enhancement Preprocessing IEEE TCSVT | OpenCV, PyTorch, EnlightenGAN / Zero-DCE, YOLO |
| 06 | TrackingSingle-Object Visual Tracking with Siamese Networks (SiamRPN / TransT) IEEE TIP | PyTorch, OpenCV, OTB / LaSOT benchmarks |
| 🏃 Action Recognition & Temporal Modelling — IEEE TMM / TIP / CVPR 2026 | ||
| 07 | ActionVideo Action Recognition with 3D CNNs (I3D / SlowFast) on Kinetics / UCF101 IEEE TIP | PyTorch, TorchVision, Kinetics, OpenCV |
| 08 | ActionTransformer-Based Video Action Recognition (TimeSformer / Video Swin) IEEE TMM | PyTorch, MMAction2, Kinetics-400 |
| 09 | ActionSkeleton-Based Action Recognition using Graph Convolutional Networks IEEE TIP | PyTorch, OpenPose / MediaPipe, NTU RGB+D |
| 10 | ActionReal-Time Human Activity Recognition for Smart Surveillance IEEE Access | MediaPipe, OpenCV, TensorFlow Lite, Python |
| 11 | ActionTemporal Action Localisation in Untrimmed Videos (ActivityNet style) IEEE TCSVT | PyTorch, ActivityNet, BMN / G-TAD concepts |
| 12 | ActionFall Detection from RGB Video for Elderly Care using Lightweight CNN IEEE Access | OpenCV, TensorFlow / PyTorch, custom dataset |
| 📦 Video Compression & Codecs — IEEE TCSVT / TIP / ICIP 2026 | ||
| 13 | CompressionLearned Video Compression with Neural Network Codecs IEEE TCSVT | PyTorch, CompressAI, FFmpeg, PSNR/SSIM/VMAF |
| 14 | CompressionH.265 / HEVC vs AV1 Rate-Distortion Comparison on HD/4K Content IEEE Access | FFmpeg, x265, libaom, VMAF, Python |
| 15 | CompressionROI-Based Adaptive Bit Allocation for Surveillance Video Coding IEEE TIP | OpenCV, FFmpeg, Python, detector for ROI |
| 16 | CompressionLow-Latency Video Streaming Optimisation with Adaptive Bitrate IEEE TMM | FFmpeg, GStreamer, WebRTC concepts, Python |
| 17 | CompressionPerceptual Quality Assessment Metrics for Compressed Video IEEE TIP | VMAF, PSNR, SSIM, Python, FFmpeg |
| ✨ Video Super-Resolution & Enhancement — IEEE TIP / TCSVT / Access 2026 | ||
| 18 | SRVideo Super-Resolution with Recurrent and Optical-Flow-Based Networks IEEE TIP | PyTorch, BasicVSR / EDVR, OpenCV, REDS dataset |
| 19 | SRReal-Time Single-Image Super-Resolution for Mobile Video Upscaling IEEE Access | PyTorch, ESRGAN / Real-ESRGAN, TensorRT, OpenCV |
| 20 | EnhanceLow-Light Video Enhancement with Retinex-Inspired Deep Models IEEE TIP | PyTorch, OpenCV, SID / LOL datasets |
| 21 | EnhanceVideo Denoising using Spatio-Temporal CNNs IEEE TCSVT | PyTorch, OpenCV, DAVIS / custom noise data |
| 22 | EnhanceDeblurring of Motion-Blurred Video Frames with Deep Deconvolution IEEE TIP | PyTorch, OpenCV, GoPro / REDS deblur |
| 23 | SRSpace-Time Video Super-Resolution (Joint Spatial and Temporal Upsampling) IEEE TIP | PyTorch, Zooming Slow-Mo concepts, OpenCV |
| 📹 Surveillance, Anomaly Detection & Behaviour Analysis — IEEE TIFS / Access 2026 | ||
| 24 | SurveillanceVideo Anomaly Detection with Autoencoders and Memory Modules IEEE TIP | PyTorch, OpenCV, UCSD / Avenue / ShanghaiTech |
| 25 | SurveillanceCrowd Density Estimation and Counting from Surveillance Cameras IEEE TCSVT | PyTorch, CSRNet / CANNet, ShanghaiTech dataset |
| 26 | SurveillancePerson Re-Identification across Non-Overlapping Camera Views IEEE TIP | PyTorch, Torchreid, Market-1501 / DukeMTMC |
| 27 | SurveillanceViolence / Fight Detection in Surveillance Video Streams IEEE Access | OpenCV, PyTorch, RWF-2000 / Hockey datasets |
| 28 | SurveillanceAbandoned Object Detection with Background Modelling and Tracking IEEE Access | OpenCV, MOG2 / KNN background, Python |
| 29 | SurveillanceFace Mask and Social-Distancing Monitoring System from CCTV IEEE Access | YOLOv8, OpenCV, Python, custom dataset |
| 🏥 Medical & Biomedical Video Analysis — IEEE TMI / JBHI / Access 2026 | ||
| 30 | MedicalPolyp Detection and Segmentation in Colonoscopy Videos IEEE TMI | PyTorch, U-Net / PraNet, OpenCV, CVC / Kvasir |
| 31 | MedicalSurgical Tool Detection and Tracking in Laparoscopic Video IEEE JBHI | YOLOv8, DeepSORT, PyTorch, Cholec80 / EndoVis |
| 32 | MedicalRetinal Vessel Segmentation from Fundus Video / Image Sequences IEEE TIP | PyTorch, U-Net, DRIVE / STARE datasets |
| 33 | MedicalCardiac Motion Analysis from Echocardiography Sequences IEEE TMI | MATLAB / PyTorch, OpenCV, EchoNet concepts |
| 34 | MedicalSkin Lesion Tracking and Change Detection from Dermoscopic Video IEEE Access | OpenCV, PyTorch, ISIC-style data |
| 🧩 Video Segmentation & Semantic Understanding — IEEE TIP / CVPR 2026 | ||
| 35 | SegmentationVideo Object Segmentation (Semi-Supervised / One-Shot) IEEE TIP | PyTorch, STM / AOT, DAVIS, YouTube-VOS |
| 36 | SegmentationReal-Time Semantic Segmentation of Road Scenes for Autonomous Driving IEEE TITS | PyTorch, DeepLabv3+ / BiSeNet, Cityscapes |
| 37 | SegmentationInstance Segmentation in Crowded Video Scenes IEEE TIP | Detectron2 / Mask R-CNN, PyTorch, COCO / CrowdHuman |
| 38 | SegmentationBackground Subtraction with Deep Learning for Dynamic Scenes IEEE Access | OpenCV, PyTorch, CDnet / LASIESTA |
| ⚡ Edge AI · Real-Time Video · Deployment — IEEE Access / IoT-J 2026 | ||
| 39 | EdgeTensorRT Optimisation of YOLOv8 for Real-Time Inference on Jetson / GPU IEEE Access | YOLOv8, TensorRT, CUDA, Jetson / RTX, OpenCV |
| 40 | EdgeMobile Video Analytics Pipeline with TensorFlow Lite / ONNX Runtime IEEE Access | TFLite, ONNX, OpenCV, Android / Raspberry Pi |
| 41 | EdgeFrame-Skipping and Model Cascade for Energy-Efficient Video Analytics IEEE IoT-J | PyTorch, OpenCV, power profiling scripts |
| 42 | EdgeMulti-Camera Edge Processing with Synchronised Streams IEEE Access | GStreamer, OpenCV, MQTT / RTSP, Python |
| 📐 3D Vision · Depth · Multi-View Video — IEEE TIP / 3DV 2026 | ||
| 43 | 3DMonocular Depth Estimation from Video with Temporal Consistency IEEE TIP | PyTorch, MiDaS / Depth Anything, OpenCV |
| 44 | 3DStereo Matching and Disparity Map Refinement for Depth from Dual Cameras IEEE TIP | OpenCV, PyTorch (RAFT-Stereo concepts), Middlebury |
| 45 | 3DHuman Pose Estimation and 3D Lifting from Single RGB Video IEEE TCSVT | MediaPipe / OpenPose, PyTorch, Human3.6M |
| 46 | 3DOptical Flow Estimation with RAFT and Application to Motion Analysis IEEE TIP | PyTorch, RAFT, OpenCV, Sintel / KITTI |
| 🎨 Restoration · Style · Multimodal · Evaluation — IEEE TIP / Access 2026 | ||
| 47 | RestoreVideo Inpainting for Object Removal and Content Completion IEEE TIP | PyTorch, OpenCV, DAVIS / YouTube-VOS inpaint |
| 48 | StyleNeural Style Transfer for Artistic Video Stylisation with Temporal Coherence IEEE Access | PyTorch, OpenCV, style transfer models |
| 49 | RestoreOld Film / Archive Video Restoration (Denoise + Colourise + Stabilise) IEEE Access | OpenCV, FFmpeg, PyTorch colourisation nets |
| 50 | DetectionLicense Plate Recognition from Video with Detection + OCR Pipeline IEEE Access | YOLOv8, EasyOCR / PaddleOCR, OpenCV |
| 51 | ActionSign Language Recognition from Continuous Video Streams IEEE Access | MediaPipe, PyTorch, WLASL / custom dataset |
| 52 | SurveillanceTraffic Flow and Vehicle Type Classification from Roadside Cameras IEEE TITS | YOLOv8, OpenCV, DeepSORT, Python |
| 53 | CompressionPerceptual Loss Functions for Learned Image/Video Compression IEEE TCSVT | PyTorch, CompressAI, LPIPS, VMAF |
| 54 | EdgePrivacy-Preserving Video Analytics with On-Device Face Blurring IEEE Access | OpenCV, MediaPipe, YOLO, Raspberry Pi / Jetson |
| 55 | SegmentationMoving Object Segmentation without Background Model (Motion-Based) IEEE TIP | OpenCV, optical flow, Python |
| 56 | MedicalEndoscopic Image Quality Assessment and Enhancement Pipeline IEEE JBHI | OpenCV, PyTorch, custom endoscopy data |
| 57 | ActionSports Action Classification from Broadcast Video (Cricket / Football) IEEE Access | PyTorch, OpenCV, custom or public sports datasets |
| 58 | SRFace Video Super-Resolution for Recognition under Low Resolution IEEE TIP | PyTorch, GFPGAN / CodeFormer concepts, OpenCV |
| 59 | EnhanceVideo Stabilisation using Feature Tracking and Motion Compensation IEEE Access | OpenCV, FFmpeg, Python |
| 60 | DetectionMulti-Class Traffic Sign Detection and Recognition from Driving Video IEEE TITS | YOLOv8, OpenCV, GTSRB / custom driving data |
Topics are aligned with recent trends in IEEE Transactions on Image Processing, IEEE TCSVT, IEEE Transactions on Multimedia, IEEE Access, CVPR, ICCV and ICIP. Contact us for the specific base paper reference, complete source code, trained models, metrics, university-format report, PPT and viva Q&A for any topic above.
Why Choose Us for IEEE Video Processing Projects?
Bangalore-based guidance for BE, BTech and MTech video processing and computer vision projects.
Detection & Tracking
YOLOv8, DeepSORT, ByteTrack, Siamese trackers and custom datasets — complete pipelines with mAP, MOTA metrics and IEEE base paper alignment for TIP / Access style projects.
Action & Temporal Models
3D CNNs, SlowFast, Video Transformers, skeleton GCNs and temporal action localisation — PyTorch code, Kinetics/UCF101 experiments and TMM / TIP oriented evaluation.
Compression & Quality
Learned codecs, HEVC/AV1 RD curves, ROI coding and VMAF-based quality assessment — FFmpeg + PyTorch stacks matching IEEE TCSVT research themes.
Edge & Real-Time Deployment
TensorRT, TFLite, ONNX Runtime and Jetson pipelines for real-time video AI — latency, FPS and power measurements suitable for IEEE Access / IoT-J style reports.
Frequently Asked Questions — IEEE Video Processing Projects
Top topics include real-time multi-object tracking with YOLOv8 and DeepSORT, video action recognition using 3D CNNs or Transformers, learned video compression, video super-resolution, anomaly detection in surveillance, medical endoscopy analysis, semantic video segmentation, and edge deployment with TensorRT.
OpenCV, PyTorch, TensorFlow/Keras, YOLO (v5/v8/v11), Detectron2, MMDetection, FFmpeg, MATLAB Computer Vision Toolbox, MediaPipe, GStreamer, CUDA/TensorRT, and standard datasets (Kinetics, COCO, MOTChallenge, UCF101, DAVIS, Cityscapes).
Yes. Topics match recent trends in IEEE Transactions on Image Processing, IEEE TCSVT, IEEE Transactions on Multimedia, IEEE Access, CVPR, ICCV, ECCV, ICIP and related venues. Base paper references are provided with each package.
Yes. Packages include IEEE base paper reference, source code (Python/OpenCV/PyTorch), trained models where applicable, quantitative metrics, university-format report (VTU/Anna/JNTU), PPT and viva Q&A.
Video Processing & Vision Lab — Bangalore
GPU workstations, camera capture setups, Jetson edge boards and consultation desks for BE, BTech and MTech video processing scholars.
GPU Training
PyTorch / YOLO
Deep Learning RigsPyTorch / YOLO
OpenCV / FFmpeg
Processing Lab
Classical + Modern CVProcessing Lab
Jetson / TensorRT
Edge Inference
Real-Time DeploymentEdge Inference
Surveillance &
Multi-Camera Setup
Tracking & AnomalyMulti-Camera Setup
Medical Video
Analysis Bench
Endoscopy / FundusAnalysis Bench
Compression &
Quality Metrics
Codec EvaluationQuality Metrics
Action / Pose
Recognition
Temporal ModelsRecognition
Viva & Report
Preparation
Documentation SupportPreparation