Object tracking

The computer vision task of identifying and following objects across consecutive video frames while maintaining their identity and spatial relationships.

Core techniques:

• Feature-based tracking: Using SIFT, ORB, or deep features for frame-to-frame matching
• Deep learning trackers: Siamese networks (e.g., SiamRPN), correlation filter-based methods
• Multi-object tracking (MOT): Handling occlusions, identity switches, and scale changes (e.g., SORT, DeepSORT)

Recent advancements focus on integrating spatial-temporal understanding with language models:

• VideoRefer Suite (Alibaba, Apache 2 license): Enhances Large Language Models (LLMs) with fine-grained spatial-temporal object understanding, enabling precise object tracking and reasoning within video sequences. [See: 2026 04 14 Fahd Mirza Videorefer model running locally]

Related concepts: Video understanding, Multi-object tracking, Spatial-temporal modeling, large-language-models