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Open research questions in Video Surveillance and Tracking Methods

166 gap statements mined from Video Surveillance and Tracking Methods papers in our 4.5M-paper local library, which holds 2,155 papers on the topic — drawn mostly from each paper's own stated research gap, future-work, challenge and limitation notes, and its abstract. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one.

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What the literature leaves open

  • Prior work has not effectively addressed the challenges of visual object tracking, such as deformation, occlusion, and scale variation. There is a need for a novel approach that integrates locality-aware attention mechanisms to improve tracking performance.

    LATrack: enhancing transformer visual tracking via locality-aware attention · 2026 · DOI

  • The lack of consideration of trajectory features in existing detection methods. The need for a more accurate and reliable method to detect and track drones in aerial surveillance video frames.

    Improving visual differentiation of drones and birds in aerial surveillance using trajectory features · 2026 · DOI

  • Limited discriminative capability of global feature representation. Part localization inaccuracies and challenges associated with detailed part-level feature representation.

    Strategic Feature Integration for Superior Person Re-ID: A Part-Based Approach · 2026 · DOI

  • Need for more effective mechanisms to address part localization inaccuracies and enhance discriminative part-level feature representation. Inadequacy of traditional frameworks in addressing the complexities of identity recognition in varied surveillance contexts.

    Strategic Feature Integration for Superior Person Re-ID: A Part-Based Approach · 2026 · DOI

  • There is an urgent need for robust contingency management systems, such as Anti-UAV technologies, to ensure safe air traffic. The integration of UAVs into existing airspace frameworks presents unique challenges, particularly regarding safety and security. Current detection algorithms have limitations, particularly in terms of scale variance.

    Recent Research Progress on Ground-to-Air Vision-Based Anti-UAV Detection and Tracking Methodologies: A Review · 2025 · DOI

  • Further research can be done to improve the precision and robustness of tracking algorithms. Research on lightweight networks can be continued to focus on model compression, architecture design, knowledge distillation and applications.

    SiamCTCA: Cross-Temporal Correlation Aggregation Siamese Network for UAV Tracking · 2025 · DOI

  • The need for more effective and decentralized detection systems. The lack of integration of AI and multiple sensors in existing detection systems. The need for a system that can be powered by solar energy and communicate using LoRa/LoRaWAN.

    Development of a Solar-Powered Edge Processing Perimeter Alert System with AI and LoRa/LoRaWAN Integration for Drone Detection and Enhanced Security · 2025 · DOI

  • The lack of effective methods for cross-view target identity association in low-altitude scenes involving UAVs. The need for a model that can leverage the unique characteristics of UAVs to improve multi-view, multi-target tracking.

    Multi-View, Multi-Target Tracking in Low-Altitude Scenes with UAV Involvement · 2025 · DOI

  • The paper also identifies the challenge of adapting to dynamic environments, where the method needs to quickly adjust to new tasks and scenes.

    Cross-Scene Multi-Object Tracking for Drones: Leveraging Meta-Learning and Onboard Parameters with the New MIDDTD · 2025 · DOI

  • The direct application of conventional background modeling or motion segmentation methods may yield suboptimal performance in UAV contexts. The need for a method that can effectively mitigate false positives caused by motion parallax and platform movement. The lack of a benchmark for UAV moving object detection.

    An Unsupervised Moving Object Detection Network for UAV Videos · 2025 · DOI

  • Aerial target tracking requires high precision and strong robustness due to complex scenarios.

    SiamCTCA: Cross-Temporal Correlation Aggregation Siamese Network for UAV Tracking · 2025 · DOI

  • Existing tracking systems have shortcomings in capturing temporal relationships between consecutive frames. Traditional tracking algorithms primarily deal with relatively stable changes in viewpoints and target motion. The potential of spatio-temporal information is far from being fully explored.

    Spatio-Temporal Feature Aware Vision Transformers for Real-Time Unmanned Aerial Vehicle Tracking · 2025 · DOI

  • Global trackers cannot maintain approximate consistency between target sizes in the template and the search region. Existing global trackers have complex structures and require two rounds of feature fusion, making them unable to run in real time.

    Enhancing the Scale Adaptation of Global Trackers for Infrared UAV Tracking · 2025 · DOI

  • Centralized architectures are not ideal due to high cost, processing time issues, and network bandwidth overhead. Traditional CNNs may not be the optimal solution for video processing. 3D-CNNs are computationally expensive and not suitable for real-time violence recognition on lightweight devices.

    LAVID: A Lightweight and Autonomous Smart Camera System for Urban Violence Detection and Geolocation · 2025 · DOI

  • Incorporating temporal dynamics into attention mechanisms - Incorporating motion-based cues into attention mechanisms - Incorporating stronger temporal cues (e.g., motion consistency across frames) - Incorporating more discriminative appearance…

    LATrack: enhancing transformer visual tracking via locality-aware attention · 2026 · DOI

  • Existing methods often restrict the flow of spatiotemporal information to fixed-length or single-stage representations. The neglect of temporal information inherent in video sequences. The limitation of single-stage designs that overlook spatiotemporal features across multiple stages.

    Mamba-driven context-aware tracking with dual prompts · 2026 · DOI

  • DPP does not retain persistent or content-conditioned positional information - The complete-model cost is high at 132.28 GFLOPs and 14.86 ms per 256×256 input - The resulting 33.86 M parameters restrict deployment in resource-constrained settings - The reported results are based on single runs without a fixed random seed - The results are limited to three crowd counting benchmarks, leaving run-to-run variability…

    Bidirectional Cross-Level Feature Interaction and Context-Aware Multi-Scale Attention for Crowd Counting · 2026 · DOI

  • Identifying key technological gaps, - Highlighting promising directions for future research and development in Anti-UAV technologies, - Exploring various Anti-UAV systems being developed and deployed…

    Recent Research Progress on Ground-to-Air Vision-Based Anti-UAV Detection and Tracking Methodologies: A Review · 2025 · DOI

  • Investigating the system's performance in detecting drones in real-world scenarios. Improving the system's detection accuracy in the presence of environmental noise. Exploring the potential for detecting helicopters at greater distances.

    Development of a Solar-Powered Edge Processing Perimeter Alert System with AI and LoRa/LoRaWAN Integration for Drone Detection and Enhanced Security · 2025 · DOI

  • The inherent domain gap between aerial and ground views, - The lack of extensive labeled data, - The complexity of group-level interactions and the arrangement of group…

    Unsupervised Aerial-Ground Re-Identification from Pedestrian to Group for UAV-Based Surveillance · 2025 · DOI

  • The lack of ground-truth annotations complicates the task of cross-modality and viewpoint-heterogeneous ReID, - Existing unsupervised Re-ID methods for UAVs primarily focus on aerial single-modality scenarios, - The view discrepancy between the aerial and ground scenarios results in a view-dependent feature space, - The proposed method may not perform well in scenarios with significant variations in lighting, pose…

    Unsupervised Aerial-Ground Re-Identification from Pedestrian to Group for UAV-Based Surveillance · 2025 · DOI

  • Enhance the system's performance and processing speed by integrating a compact AI accelerator - Improve communication between smart cameras to effectively monitor objects and events - Harness the power of massive data more effectively by automating the review process of video…

    LAVID: A Lightweight and Autonomous Smart Camera System for Urban Violence Detection and Geolocation · 2025 · DOI

  • Limited to edge devices such as NVIDIA Jetson Orin Nano and Raspberry Pi 5, - Requires specific camera setups…

    Smart Wildlife Monitoring: Real-Time Hybrid Tracking Using Kalman Filter and Local Binary Similarity Matching on Edge Network · 2025 · DOI

  • Further optimization for other edge devices, - Exploration of other object detection models for wildlife monitoring, - Investigation of the system's performance in different environmental…

    Smart Wildlife Monitoring: Real-Time Hybrid Tracking Using Kalman Filter and Local Binary Similarity Matching on Edge Network · 2025 · DOI

  • Then, we enhance the robustness of sparse data feature extraction using two strategies: on one hand, we utilize Anti-Noise Contour Enhancement (ANCE) module to improve motion contour features and mitigate sensor pulse noise; on the other hand, we implement Direction-Aware Sparse Perception (DASP) module to encourage the model to extract robust person descriptors.

    Sparse VMamba: Robust Spatio-Temporal Information Modeling for Event Camera Person Re-Identification · 2026 · DOI

Most-cited papers in Video Surveillance and Tracking Methods

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Open questions raised by papers listed on this page include: (1) There is a need for a novel approach that integrates locality-aware attention mechanisms to improve tracking performance (“LATrack: enhancing transformer visual tracking via locality-aware attention”, 2026); (2) The lack of consideration of trajectory features in existing detection methods (“Improving visual differentiation of drones and birds in aerial surveillance…”, 2026); (3) The lack of integration of AI and multiple sensors in existing detection systems (“Development of a Solar-Powered Edge Processing Perimeter Alert System with AI…”, 2025); (4) The lack of effective methods for cross-view target identity association in low-altitude scenes involving UAVs (“Multi-View, Multi-Target Tracking in Low-Altitude Scenes with UAV Involvement”, 2025). 166 gap statements have been mined from Video Surveillance and Tracking Methods papers in our 4.5M-paper local library, which holds 2,155 papers on the topic; the gaps come from whichever of those papers state one. They are mostly the research gaps the authors state and the papers' abstracts, plus future-work, limitations and challenges passages. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one, so you can read the original claim in context.

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