The Applicability of Spatiotemporal Oriented Energy Features to Region Tracking
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Bibliographic record
Abstract
This paper proposes the novel application of an uncommonly rich feature representation to the domain of visual tracking. The proposed representation for tracking models both the spatial structure and dynamics of a target in a unified fashion, while simultaneously offering robustness to illumination variations. Specifically, the proposed feature is derived from spatiotemporal energy measurements that are computed by filtering in 3D, (x, y, t), image spacetime. These spatiotemporal energy measurements capture the underlying local spacetime orientation structure of the target across multiple scales. The breadth of applicability of these features within the field of visual tracking is demonstrated by their instantiation within three disparate tracking paradigms that are representative of the various basic types of region trackers in the field. Instantiation within these three tracking paradigms requires that the raw oriented energy measurements be post-processed using different methodologies that range from histogram accumulation to the identity transform. Qualitative and quantitative empirical evaluation on a challenging suite of videos demonstrates the strength and applicability of the proposed representation to tracking, as it outperforms other commonly-used features across all tracking paradigms. Moreover, it is shown that overall high tracking accuracy can be obtained with this proposed representation, as spatiotemporal oriented energy instantiations are shown to outperform several recent, state-of-the-art trackers.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it